Social-Media

Theoretische Überlegungen allein ergeben kein vollständiges Bild von der Digitalisierung in Verwaltungen. Deshalb ist es sinnvoll, zusätzlich Wahrnehmungen, Stimmungen und Ideen aus den unterschiedlichen Ecken der Verwaltungswelt einzufangen. Im Folgenden kommen Menschen zu Wort, die den digitalen Wandel im öffentlichen Dienst am eigenen Leib erfahren. Die Bandbreite der neun Interviewpartnerinnen und -partner reicht dabei von Führungskräften zu Mitarbeitenden, von Generation Z bis zu den Baby Boomern.

Die Digitalisierung bringt für Verwaltungen fünf grundlegende Trends mit sich:

This chapter discusses Amartya Sen’s capability approach in relation to financial capabilities. It zooms in on the behavioural dimensions behind the financial crisis, but also on why consumers do not yet trust banks today. The chapter uses survey data of Dutch bankers to show that the regulation after the crisis has not helped bankers to use their moral compass. This is, paradoxically, due to a lack of autonomy. Bankers are generally not irresponsible persons but the pressure of targets, the detailed compliance procedures, and the lack of moral leadership in banks constrain them in using their moral compass. Also, at the consumers’ side, capabilities are lacking. Consumers tend to suffer from decision-making stress in combination with widely available credit and insufficient financial knowledge. The capabilities of some disadvantaged groups may, for example, be strengthened with earning opportunities in the community economy and community currency systems.

The Introduction explains that this book was written in response to the lack of change in economics following the 2008 financial crisis. It is a response to the absence of imagination of a noncapitalist economy and lack of interest in the rich diversity of economic thought of 250 years of history of economics and what these ideas can bring for reflecting on a postcapitalist economy. The book hopes to inspire economists and noneconomists alike to reflect on feasible economic ideas and practices for a more stable and sustainable economy.

As the Feeling Economy emerges, and AI assumes more thinking tasks, people are increasingly focusing on emotion. One notable way this trend is manifested is the increasing use of emoticons (typographical tricks that resemble pictures) and emoji (plug-in graphics that are actual pictures). Such emotional communication has become ubiquitous on social media and the Internet. Those technologies have deconstructed time, physical distance, and emotional distance, making emotional connection possible even when people are far apart, and even when their communication is separated in time. This greater access to emotional communication makes emotional intelligence more important than ever. We even see the emotionalization of the creative arts, such as music, as AI becomes more involved in artistic production.

Management innovation refers to the implementation of management ideas, practices, tools, or structures that are new to the adopting organization. Organizational performance and other innovation successes are found to be closely related to management innovation. Organizations all over the world, hence, are constantly looking to invent or adopt management innovation in their organizations. With the role of change agents, HRD professionals are increasingly involved in management innovation. Yet, the success rate for implementing management innovation is low and our knowledge on management innovation in Vietnam is limited. In this chapter, we provide an introduction to management innovation and its determinants and development in Vietnam. We describe emerging management innovations in Vietnam and discuss several challenges for their implementation in which organizational culture appears to be a critical factor. Further implications for research and practice are also presented.

As people increasingly delegate their thinking tasks to AI based in the Internet and accessible by smartphones and digital assistants, their thinking abilities atrophy. This means that the best way to reach people is now through their emotions. As a result, as the electorate becomes more feeling-oriented, political campaigns and political candidates are also becoming more feeling-oriented. This explains the rise of so many populist politicians around the world, as well as the rise (and predicted fall) of US President Donald Trump.

SentiProMo is a novel social business process modeling tool enabled by sentiment analysis. We designed and developed SentiProMo for supporting social business processes management to enhance the business process management (BPM) lifecycle. In particular, we socially improve the BPM lifecycle in the process analysis stage by capturing and processing stakeholder’s opinions regarding the tasks within a business process. By taking a social information systems perspective, SentiProMo transforms these opinions with sentiment analysis and classifies them into positive and negative feedback. The aim is to support the business analysts for redesigning a business process by considering the sentiment-analyzed opinions for designing the to-be process. We illustrate the current SentiProMo’s capabilities with a simple process.

In recent years, the frequency of organizational change increased due to internal innovation and external forces. Classical enterprise life cycle theories expect infrequent, large-scale implementations that lead to costly and risk-intensive shakedowns after implementation. Currently, most process support systems turn to cloud solutions, and integrated systems are used as one consolidated enterprise system (ES). Processes and organizational routines are the unit of analysis for organizational change, and the BPM life cycle captures the phases involved in changing them. We apply the perspective of an ES vendor to enable sustained support within the same ES, despite inevitable change. Hence, for each phase, we identify integral and supporting capabilities, and derive corresponding features in an ES. This view is also useful to potential users to analyze vendors in regard to capabilities for expected change.

Due to BRI, Costa Rica and China will promote bilateral cooperation to improve exchanges of goods, technology, capital, and personnel through mutual connectivity and mutual learning. Both countries have joined efforts to promote investment in different economic sectors and boost better opportunities for those enterprises that wish to enter and compete in the market. China became one of the most important protagonists of international cooperation as part of the new cooperation roles. This chapter presents introduction on national policy for developing SMEs in Costa Rica and an overview of developing levels of local SMEs. It points out that BRI has become a cooperation platform for Costa Rica and its SMEs through policy coordination, technology access and exchanges, industrial parks or economic and commercial cooperation zones, facilities connectivity and capacity building, training, and innovation.

Agent-based simulations of social media platforms often need to be run for many repetitions at large scale. Often, researchers must compromise between available computational resources (memory, run-time), the scale of the simulation, and the quality of its predictions.As a step to support this process, we present a systematic exploration of simplifications of agent simulations across a number of dimensions suitable for social media studies. Simplifications explored include sub-sampling, implementing agents representing teams or groups of users, simplifying agent behavior, and simplifying the environment.We also propose a tool that helps apply simplifications to a simulation model, and helps find simplifications that approximate the behavior of the full-scale simulation within computational resource limits.We present experiments in two social media domains, GitHub and Twitter, using data both to design agents and to test simulation predictions against ground truth. Sub-sampling agents often provides a simple and effective strategy in these domains, particularly in combination with simplifying agent behavior, yielding up to an order of magnitude improvement in run-time with little or no loss in predictive power. Moreover, some simplifications improve performance over the full-scale simulation by removing noise.We describe domain characteristics that may indicate the most effective simplification strategies and discuss heuristics for automatic exploration of simplifications.

In diesem Kapitel werden die Möglichkeiten der künstlichen Intelligenz im Vertriebsbereich genauer erläutert und konkretisiert. Dafür werden die unzähligen KI-Tools und ihre Anwendungsmöglichkeiten in 20 Überkategorien zusammengefasst, die detailliert beschrieben werden. Sie erfahren, wie KI-Systeme die jeweiligen Vertriebstätigkeiten und -prozesse verbessern können und welche konkreten Anwendungsmöglichkeiten es für den Vertrieb gibt. Für jede Kategorie werden Beispiele von Tools genannt sowie auch ein konkretes Praxisbeispiel beschrieben. Das Kapitel soll Sie in die Lage versetzen, konkrete Möglichkeiten für den Einsatz von KI-Tools für Ihr Unternehmen zu finden. Zudem ist es das Ziel, dass Sie eine bessere Vorstellung davon bekommen, welche Potenziale die künstliche Intelligenz für den Vertriebsbereich bietet, sodass Sie konkreten Handlungsbedarf für Ihre Vertriebsorganisation ableiten können.

Der Begriff Künstliche Intelligenz ist überstrapaziert und die meisten von uns nehmen die tatsächlichen Fähigkeiten der KI falsch wahr. Künstliche Intelligenz ist nicht neu, aber erst in den letzten Jahren hat sie an Relevanz gewonnen, da erst die jüngsten technologischen Entwicklungen ihre Ausbreitung und Weiterentwicklung ermöglicht haben. KI findet schon längst bei den weltweit führenden Unternehmen Einsatz, die ihr unter anderem auch ihre Marktführerschaft zu verdanken haben. Während Google, Facebook, Amazon & Co tagtäglich von der KI-Technologie profitieren, ist sie im Mittelstand immer noch ein Mythos, der zu weit von der Realität der Unternehmen entfernt zu sein scheint. Großer Irrtum, denn KI kann heute schon auch in den kleinsten Unternehmen eingesetzt werden und dort zusätzliche oder neue Potenziale erschließen. Die fantasievolle Vorstellung, die wir über KI pflegen, hat nichts mit der Realität der Algorithmen zu tun.

Wer Künstliche Intelligenz im eigenen Vertrieb implementieren möchte, muss zunächst für die richtige Perspektive im Zusammenhang mit einer strategischen Herangehensweise sorgen. Dabei sind diverse KI-Spezifika zu beachten, unabhängig davon, ob es sich um die Entwicklung der KI-Strategie, die Schaffung von technologischen und organisatorischen Voraussetzungen für die KI-Implementierung oder um das erste KI-Projekt handelt. Die Einführung von KI in Vertriebsorganisationen ist kein Einzelprojekt, sondern eine KI-Reise, wenn man von den vielfältigen Möglichkeiten der KI-Technologie profitieren möchte. Diese Reise sollte durchdacht und strategisch geplant beginnen.

Künstliche Intelligenz bietet eine schöne neue Welt an Möglichkeiten, den Vertrieb über den gesamten Vertriebsprozess zu optimieren. Es gibt zahlreiche Tools und Anbieter, die alle Prozesse im Vertrieb unterstützen können: von der Lead-Generierung und -Qualifizierung, über Deal-Verwaltung und Kundenkommunikation bis zum Account-Management und Business Development.

Die meisten Aufgaben im Büro erreichen uns durch die unterschiedlichsten Kanäle. Manchmal kommen Aufgaben über unser E-Mail-Programm, manchmal kommen sie auf Zuruf vom Chef oder Team, aus Besprechungen, aus Telefongesprächen oder auch aus Projekten.

The main purpose of the chapter is to identify the potential of big data analysis (BDA) as a tool to enhance the tourism experience by offering products/services that are more personalised to meet each visitor’s unique needs and preferences, as well as to counteract the negative effects of overtourism. The literature review was adapted to define and estimate the significance of data-based experience management. Some examples of big data (BD) application in travel and tourism were identified (e.g. a predictive tourism experience, Internet-based tourist involvement and co-creation, personalisation of the value proposal, effectiveness improvement and promotion enhancement).

This paper aims to identify selected determinants and main areas of recreational and tourist activity of the inhabitants of rural communes of the Poznań Metropolis based on the results of a research study concerning their preferences, needs, and main areas of recreation. The following these were assumed: (1) the activity is mainly induced by the need for achieving well-being through active recreation, looking for peace, or improving health, and (2) the preferences and needs do not differ significantly, regardless of home location. A direct survey (with the technique of an interview with a questionnaire) of a group of people living in rural communes of the Poznań Metropolis was conducted. Results of the survey were subjected to statistical analysis using structure and correlation parameters and were then presented in tables, graphs, and in writing. The analysis of co-occurrence of the variables was conducted based on the Pearson’s r correlation coefficient. The inhabitants of rural communes indicated their needs concretely as looking for peace, quiet and rest, with physical recreation as the most important activity. In comparison to other inhabitants, they felt less need for physical recreation and learning about nature and culture and chose areas slightly further away from homes.

Social media (SM) are increasingly changing the context in which businesses operate, and therefore the understanding of continuously changing trends in the context of digital marketing is critical for the development of enterprises in the leisure market. Amongst those trends figures the increasing importance of SM, the growth of user-generated content and its influence, not only on travellers’ decision making but also in tourism-related enterprises’ marketing strategies that might also take into account sustainability concerns and main issues. This research aims to analyse current and future use of SM in the promotion of tourism businesses and activities, with a particular focus on sustainable tourism practices. Semi-structured interviews were adopted to identify and analyse the perceptions of owners and/or managers of leisure-related enterprises who are operating within the geographic context of Viana do Castelo Littoral Geopark. The results indicate that, overall, SM are perceived as being very important in the promotion of the business, reaching customers and enhancing interaction. However, some owners/managers do recognise their use as being complementary with Google ads, considering the perceived impacts on their sales. Currently, Facebook and Instagram are the most used SM, and the enterprises’ owners and/or managers are aware of their different objectives and audiences. In the future, all of them want to enhance SM management and professional use, with Youtube being the privileged network. In general, the owners and/or managers of the leisure-related enterprises have concerns about sustainability, and some of them do implement and promote sustainable tourism practices. However, there is a general recognition that travellers are not willing to pay more money for what are considered ‘sustainable activities”/ “experiences’. This research will discuss practical and theoretical implications about the importance and usage of SM to digitally promote natural and cultural resources in the context of leisure-related enterprises within the framework of sustainable tourism development and marketing. Limitations and future directions are also discussed.

Based on the concepts and theory that we have introduced in another paper “Social Big Data: Concepts and Theory” in this issue, we will concretely explain hypothesis generation and integrated analysis through use cases in this paper.

This paper explains the basic concepts of social big data and its integrated analysis. First, we will explain the outline and examples of the real-world data, open data, and social data that compose social big data. After we will describe interactions among the real-world data, open data, and social data, we will introduce basic concepts of an integrated analysis based on “Ishikawa concept.” Furthermore, after explaining the flow of integrated analysis in line with the basic concept, a data model approach for integrated analysis will be introduced. Based on that, integrated hypotheses and integrated analysis will be specifically explained in another paper “Social Big Data: Case Studies” in this issue through several use cases.

The social facet of information has a deciding role in our quotidian life. An abstract representation and a proper management of Online Social Networks (OSNs) constitute a new challenge for communities of researchers. In addition, the need of extending OSNs to Multimedia Social Networks (MSNs)come from the fact that the vast majority of data is unstructured and heterogeneous, making the reuse and integration of information effortful. In this chapter we propose a general high-level model to represent and manage MSNs. Our approach is based on property graph represented by a hypergraph structure due to the intrinsic multidimensional nature of social networks and semantic relations to better represent the networks contents. Using the proposed graph structure is helpful to single out several levels of knowledge analysing the relationships defined between nodes of the same or different type. Moreover, the introduction of low-level multimodal features and a formalization of their semantic meanings give a more comprehensive view of the social network structure and content. Using this approach we call the represented network Multimedia Semantic Social Networks ( $$MS^2N$$ M S 2 N ). The proposed data model could be useful for several applications and we propose a case study on cultural heritage domain.

The paper introduces a conceptualization of experience ecosystems as semantic blended spaces instantiated by the activities carried out by independent actors moving freely and at will between different products, services, devices, people, and locations in pursuit of individual goals.This conceptualization is anchored to three distinct cultural and socio-technical shifts that characterize the current postdigital condition: the displacement of postmodernism as the cultural dominant; the embodiment of digitality and the emergence of a blended space of action; the occurrence of a postdigital society.It contributes to ongoing conversations on ecosystem-level and systemic design from the point of view of information architecture and user experience in five distinct ways: by centering the discourse on the actor-driven individual experience made possible by the postdigital condition; by framing the problem space from an embodied, spatial and architectural perspective; by considering the environment systemically as a blend of digital and physical non-contiguous spaces; by recasting the object of design to be the semantic and spatial relationships that exist or could exist between the elements of the actor-centered ecosystem; by introducing a mapping methodology that can be used to capture and spatially describe the relational complexity of said ecosystems for further intervention.

Genocide denial is a way in which to diminish the atrocities that have occurred and forget about the victims. This behavior has been hypothesized to lead to reoccurrence of genocide. Denial permits people to forget and when no survivors are left all that remains is memory. When memory is attacked and denied, the possibility of reoccurrence emerges.As a criminal aspect, many European countries have criminalized genocide denial. The reasoning for this is to protect memory and honor the victims. These reasons counteract the goal of denial which is usually to forget. As such these laws have a place in our understanding of genocide denial.

This chapter is designed to explain the methods available to respond to genocide. This can include military or political intervention during an ongoing genocide or a legal response after a genocide has occurred. By exploring the Rwandan and Kosovo situations we understand that the UN response to genocide is not enough to prevent its occurrence. Following the disastrous response to the Rwandan genocide much work was put into what became known as R2P—the responsibility to protect.A discussion of how individuals can respond to genocide includes simple actions one can take when confronted with genocide. The goal of this chapter is to explore how to respond to genocide and not whether we should respond.

Development of energy infrastructure has long been pivotal in shaping contemporary issues in China, and geographically uneven development is a perennial challenge for central, provincial, and local government organs. As China has moved away from reliance on coal power in favour of renewable electricity generation, hydroelectricity development has increased substantially, notably over the last decade. Though many large dams have become mired in a range of social, political, and environmental concerns, small operations have proliferated rapidly. One valuable but insufficiently understood factor in this rapid development of small dams is government rhetoric linking electrification with social change in underdeveloped rural areas, particularly among ethnic minority groups. Consequently, small hydropower-based electrification now reflects an integral component for initiatives promoting development and the modernisation of communities deemed ‘backward’. A lack of empirical field-based research, however, has left gaps in our understanding of on-the-ground outcomes, specifically how electrification has influenced the everyday lives of rural and ethnic minority households. This chapter reflects on seven years of ethnographic fieldwork conducted in the Nu River Valley of Yunnan Province, providing insights into how small, rural ethnic minority communities navigate and negotiate modernisation processes resulting from the development of small hydroelectric operations and electricity provision.

This chapter rethinks citizenship and migrant subjectivities in the context of dam development in China. In detail we answer the following questions: How have the rationalities put forth by Chinese dam resettlement policies changed since the 1980s? Which new practices have evolved that are used to form dam migrant subjects? And which types of citizenship are produced as a consequence? Building upon previous studies that have shown how China has applied a graduated citizenship approach towards internal migrants and national minorities, we argue that post-resettlement support schemes such as ‘Constructing a Beautiful Home’ (meili jiayuan jianshe) introduce new forms of social citizenship that further differentiate society. This scheme builds on pastoral and benevolent technologies of government aimed at reducing the perceived risk of social instability by reintegrating affected households into the Chinese national development narrative. In doing so, the scheme establishes a neo-socialist governmentality that further marginalises dam migrants. We show that new programmes implemented in dam resettlement villages are designed to create self-responsible and docile migrant subjects that are proud of their new identity rather than contesting it.

Kay Coles James, President of The Heritage Foundation in Washington, DC, explores the history, evolution and future of think tanks Future of Think Tanks and Policy Advice in the United States.

Slim Bahrini, Executive Director of the Maghreb Economic Forum in Maghreb, Tunisia, explores the Future of Think Tanks and Policy Advice around the World.

James McGann, Director of the Think Tanks and Civil Societies Program, Lauder Institute for Management and International Studies, University of Pennsylvania in Philadelphia, PA, explores the Future of Think Tanks and Policy Advice around the World.

Somkiat Tangkitvanich, President of the Thailand Development Research Institute in Bangkok, Thailand, explores the Future of Think Tanks and Policy Advice around the World.

James McGann, Director of the Think Tanks and Civil Societies Program, Lauder Institute for Management and International Studies, University of Pennsylvania in Philadelphia, PA, explores the Future of Think Tanks and Policy Advice around the World.

James McGann, Director of the Think Tanks and Civil Societies Program, Lauder Institute for Management and International Studies, University of Pennsylvania in Philadelphia, PA, explores Think Tanks, Policy Advice, and Governance in the United States.

Roland Schmidt, Director of the Frederick Ebert Stiftung (FES) in Bonn, Germany, explores the Future of Think Tanks and Policy Advice around the World.

Edward P. Djerejian, Director and Moshe Y. Vardi, Faculty Scholar at the Baker Institute for Public PolicyHouston, TX, explore the Future of Think Tanks and Policy Advice in the United States.

Kenneth R. Weinstein, President and CEO of The Hudson Institute in Washington, DC, explores the Future of Think Tanks and Policy Advice in the United States.

Ufo Okeke-Uzodike, Executive Director of the African Heritage Institution in Enugu, Nigeria, explores the Future of Think Tanks and Policy Advice around the World.

Carlos Ivan Simonsen Leal, President and Marlos Correia de Lima , Executive Director of Fundação Getúlio Vargas in Rio de Janeiro, Brazil, explores the Future of Think Tanks and Policy Advice around the World.

Daniel Rothschild, Executive Director of the Mercatus Center at George Mason University in Arlington, VA, explores the Future of Think Tanks and Policy Advice in the United States.

James Manyika, Chairman of the McKinsey Global Institute in San Francisco, CA explores the Future of Think Tanks and Policy Advice in the United States.

Niels Veldhuis, President of the Fraser Institute in Vancouver, BC, Canada, explores the Future of Think Tanks and Policy Advice around the World.

Luis Rubio and Verónica Ortiz , Mexican Council on Foreign Relations (COMEXI) in Mexico City, Mexico, explores the Future of Think Tanks and Policy Advice around the World.

Guntram Wolff, Director of Bruegel in Belgium, explores the Future of Think Tanks and Policy Advice around the World.

Michael D. Rich, President and Chief Executive Officer of the RAND Corporation in Santa Monica, CA, explores the Future of Think Tanks and Policy Advice in the United States.

Aaron Shull, Managing Director and General Counsel of the Centre for International Governance Innovation (CIGI) in Waterloo, Canada, explores the Future of Think Tanks and Policy Advice around the World.

Idayat Hassan, Director of the Centre for Democracy and Development in Lagos, Nigeria, explores the Future of Think Tanks and Policy Advice around the World.

Paul Salem, President of the Middle East Institute in New York, NY, explores the Future of Think Tanks and Policy Advice in the United States.

Paolo Magri, Executive Vice President and Director of the Italian Institute for International Political Studies in Milan, Italy, explores the Future of Think Tanks and Policy Advice around the World.

Rose Ngugi, Executive Director of the Kenya Institute for Public Policy Research and Analysis (KIPPRA) in Nairobi, Kenya, explores the Future of Think Tanks and Policy Advice around the World.

Adam Posen, President of the Peterson Institute for International Economics in Washington, DC, explores the Future of Think Tanks and Policy Advice in the United States.

Sarah Rosen Wartell, President of the Urban Institute in Washington, DC, explores the Future of Think Tanks and Policy Advice in the United States.

Laurent Bigorgne, Director and Francis Verillaud, Special Advisor at the Institut Montaigne in Paris, France, explore the Future of Think Tanks and Policy Advice around the World.

Peter Fischer-Bollin, Head of the Division Analysis and Consulting at Konrad Adenauer Foundation (KAS) in Berlin, Germany, explores the Future of Think Tanks and Policy Advice around the World.

Manjeet Kripalani, Executive Director; Neelam Deo, Director; and Satish Kamat, Executive Board Member of Gateway House: Indian Council on Global Relations in Mumbai, India, explore the Future of Think Tanks and Policy Advice around the World.

Wang Huiyao, Founder and President of the Center for China and Globalization in Beijing, China, explores the Future of Think Tanks and Policy Advice around the World.

Anatoliy Rachok, Adviser to the President and Yuriy Yakymenko, Director of Economic Programmes at the Razumkov Centre in Kyiv, Ukraine, explore the Future of Think Tanks and Policy Advice around the World.

James McGann, Director of the Think Tanks and Civil Societies Program, Lauder Institute for Management and International Studies, University of Pennsylvania in Philadelphia, PA, explores the Future of Think Tanks and Policy Advice in the United States.

James McGann, Director of the Think Tanks and Civil Societies Program, Lauder Institute for Management and International Studies, University of Pennsylvania in Philadelphia, PA, explores the Future of Think Tanks and Policy Advice in the United States.

John Allen, President of The Brookings Institution, Washington, DC, explores the Future of Think Tanks and Policy Advice in the United States.

Kevin Rudd, President of the Asia Society Policy Institute in New York, NY, explores the Future of Think Tanks and Policy Advice in the United States.

Ellen Laipson, Distinguished Fellow and President Emeritus at the Stimson Center, Washington, DC, explores the history, evolution and future of think tanks and policy advice in the United States.

Simon Tay, Chairman and Lee Chen Chen of the Singapore Institute for International Affairs in Singapore explore the Future of Think Tanks and Policy Advice around the World.

Amos Yadlin, Executive Director of the Institute for National Security Studies in Tel Aviv-Yafo, Israel, explores the Future of Think Tanks and Policy Advice around the World.

Samir Saran, President of the Observer Research Foundation (ORF) in New Delhi, India, explores the Future of Think Tanks and Policy Advice around the World.

Brian Finlay, President and James Siebens, Fellow at the Stimson Center, Washington, DC, explores the Future of Think Tanks and Policy Advice in the United States.

Neera Tanden, President of The Center for American Progress Washington, DC, explores the Future of Think Tanks and Policy Advice in the United States.

Dong Wang, Executive Director of the Institute for Global Cooperation and Understanding, IGCUPeking University in Beijing, China, explores the Future of Think Tanks and Policy Advice around the World.

In this contribution we provide an overview of a currently on-going project related to the development of a methodology for building economic and financial indicators capturing investor’s emotions and topics popularity which are useful to analyse the sovereign bond markets of countries in the EU.These alternative indicators are obtained from the Global Data on Events, Location, and Tone (GDELT) database, which is a real-time, open-source, large-scale repository of global human society for open research which monitors worlds broadcast, print, and web news, creating a free open platform for computing on the entire world’s media. After providing an overview of the method under development, some preliminary findings related to the use case of Italy are also given. The use case reveals initial good performance of our methodology for the forecasting of the Italian sovereign bond market using the information extracted from GDELT and a deep Long Short-Term Memory Network opportunely trained and validated with a rolling window approach to best accounting for non-linearities in the data.

Financial markets, such as the stock exchange, are known to be extremely volatile and sensitive to news published in the media. Using sentiment analysis, as opposed to using time series alone, should provide a better indication for the prospects of a given financial asset. In this work, the main goal is to quantify the benefit that can be obtained by adding sentiment analysis to predict the up or down movement of stock returns. The approach makes use of several different deep learning models, from vanilla models that rely on market indicators only, to recurrent networks that incorporate news sentiment as well. Surprisingly, the results suggest that the added benefit of sentiment analysis is diminute, and a more significant improvement can be obtained by using sophisticated models with advanced learning mechanisms such as attention.

This paper presents a preliminary analysis of cryptocurrency brands on Twitter, carried out through the Semantic Brand Score Brand Intelligence App (a tool hosted in the ENEAGRID digital infrastructure). The aim is to rank five digital coins (i.e. Bitcoin, Ethereum, Zcash, Monero, Litecoin). Web crawling, data storage and brand scoring activities require computational power. The ENEAGRID infrastructure faces this challenge in terms of computational costs, with its computing core represented by the HPC CRESCO clusters. In our methodology, we run periodic sessions of web crawling to create a database of tweets (concerning digital coins), then we use the Semantic Brand Score to evaluate cryptocurrencies relevance and study their brand image. This case study is a first step towards collaborating with experts and research communities in financial domain and opening access to ENEA Virtual Labs.

Forecasting economic and financial variables is a challenging task for several reasons, such as the low signal-to-noise ratio, regime changes, and the effect of volatility among others. A recent trend is to extract information from news as an additional source to forecast economic activity and financial variables. The goal is to evaluate if news can improve forecasts from standard methods that usually are not well-specified and have poor out-of-sample performance. In a currently on-going project, our goal is to combine a richer information set that includes news with a state-of-the-art machine learning model. In particular, we leverage on two recent advances in Data Science, specifically on Word Embedding and Deep Learning models, which have recently attracted extensive attention in many scientific fields. We believe that by combining the two methodologies, effective solutions can be built to improve the prediction accuracy for economic and financial time series. In this preliminary contribution, we provide an overview of the methodology under development and some initial empirical findings. The forecasting model is based on DeepAR, an auto-regressive probabilistic Recurrent Neural Network model, that is combined with GloVe Word Embeddings extracted from economic news. The target variable is the spread between the US 10-Year Treasury Constant Maturity and the 3-Month Treasury Constant Maturity (T10Y3M). The DeepAR model is trained on a large number of related GloVe Word Embedding time series, and employed to produce point and density forecasts.

Image, Prestige, Ansehen besitzt eine Person oder Sache zunächst nicht selbst, sondern sie entstehen durch einen Betrachtenden. Dieser interpretiert stets bestimmte Eigenschaften, die einem beobachteten Objekt innewohnen. ‚Die Chemie‘ kann also zu einem guten Teil die eigenen Eigenschaften überdenken, um so indirekt an ihrem Image zu feilen und zu polieren.

This paper presents four different mechanisms for ontology learning from Twitter data. The learning process involves the identification of entities and relations from a specified Twitter data set, which is then used to produce an ontology. The initial two methods considered, the Stanford and GATE based ontology learning frameworks, are both semi-automated methods for identifying the relations in the desired ontology. Although the two frameworks effectively create an ontology supported knowledge resource, the frameworks feature a particular disadvantage; the time-consuming and cumbersome task of manually annotating a relation extraction training data sets. As a result two other ontology learning frameworks are proposed, one using regular expressions which reduces the required resource, and one that combines Shortest Path Dependency parsing and Word Mover’s Distance to fully automate the process of creating relation extraction training data. All four are analysed and discussed in this paper.

Nowadays, the existence of several available biomedical vocabularies and standards play a crucial role in understanding health information. While there is a large number of available resources in the biomedical domain, only a limited number of resources can be utilized in the food domain. There are only a few annotated corpora with food concepts, as well as a small number of rule-based food named-entity recognition systems for food concept extraction. Additionally, several food ontologies exist, each developed for a specific application scenario. To address the issue of ontology alignment, we have previously created a resource, named FoodOntoMap, that consists of food concepts extracted from recipes. The extracted concepts were annotated by using semantic tags from four different food ontologies. To make the resource more comprehensive, as well as more representative of the domain, in this paper we have extended this resource by creating a second version, appropriately named FoodOntoMapV2. This was done by including an additional four ontologies that contain food concepts. Moreover, this resource can be used for normalizing food concepts across ontologies and developing applications for understanding the relation between food systems, human health, and the environment.

Recommendation systems, which are employed to mitigate the information overload e-commerce users face, have succeeded in aiding customers during their online shopping experience. However, to be able to make accurate recommendations, these systems require information about the items for sale and about users’ individual preferences. Making recommendations to new customers, who have no prior data in the system, is therefore challenging. This scenario, called the “cold-start problem,” hinders the accuracy of recommendations made to a new user. In this paper, we introduce the popular users personalized predictions (PUPP-DA) framework to address cold starts. Soft clustering and active learning are used to accurately recommend items to new users in this framework. Additionally, we employ deep learning algorithms to improve the overall predictive accuracy. Experimental evaluation shows that the PUPP-DA framework results in high performance and accurate predictions. Further, focusing on frequent, or so-called popular, users during our active-learning stage clearly benefits the learning process.

In regard to hazards, either produced by natural causes or by human activities, an important issue today is awareness, which is essential not only for the fast response of emergency personnel, but also for people concerned about the risks. The approach described in this chapter is based on making specialists’ knowledge accessible to the large public. This was first realized though a selection of fundamental concepts about radiological and nuclear vulnerabilities and their organization in an ontology, used for defining a website. Secondly, the rules followed for making decisions in case of hazardous events were extracted from the public reports elaborated by authorities in atomic energy, were formalized, and were implemented into a software simulator. Thirdly, the processes followed for diverse types of risks were represented graphically, to create awareness about the measurements to be taken, the actions recommended in each situation, and their timing.

We've already demonstrated how to train a character-level RNN to create original text. Now, we create a word-level RNN to analyze sentiment.

Im Folgenden möchten wir resümieren, wie sowohl fankulturell als auch wissenschaftlich mit Serienfragmenten umgegangen wird: Zuschauer_innen (oder gar Fans) sind von Serienfragmenten auf besondere Weisen emotional betroffen, Wissenschaftler_innen werden in ihrer Forschung zu Serienfragmenten mit methodischen Herausforderungen konfrontiert. Zudem werden wir in einem Ausblick Aspekte des Serienfragments festhalten, welche wir aktuell und zukünftig für besonders relevant halten. Hierbei wird uns die mehrfach wiederbelebte Serie Veronica Mars (2004–2005, 2014, 2019) als weiteres Fallbeispiel dienen.

Der Text analysiert die US-amerikanische Serie Sense8 (2015–2018), die von Lana und Lilly Wachowski mit J. Michael Straczynski für den Streamingdienst Netflix produziert wurde. Der Text diskutiert die Ästhetik der Vielfalt der Serie durch die narrative Verknüpfung acht sogenannter Sensates, die an unterschiedlichen Orten der Welt zum selben Zeitpunkt geboren und zu einem ‚Cluster‘ verbunden wurden. Zudem arbeitet der Text die Online-Kommunikation der Fan-Community nach der Absetzung der Serie im Anschluss an die zweite Staffel auf. Soziale Netzwerke funktionierten dabei als „affective publics“ (Papacharissi 2016) und stellten ein Instrument für Fans dar, um eine Öffentlichkeit zu erreichen. So konnte immerhin bewirkt werden, das Netflix nachträglich ein zweistündiges Finale beauftragte.

A virtual team (also known as a geographically dispersed team, distributed team or remote team) usually refers to a group of individuals who work together from different geographic locations and rely on communication technology such as email, FAX, and video or voice conferencing services in order to collaborate.

Name Entity Recognition is the essential tool for machine translation. Traditional Named Entity Recognition focuses on the person, location and organization names. However, there is still a lack of data to identify travel-related named entities, especially in Mongolian. In this paper, we introduce a newly corpus for Mongolian Tourism Named Entity Recognition (MTNER), consisting of 16,000 sentences annotated with 18 entity types. We trained in-domain BERT representations with the 10 GB of unannotated Mongolian corpus, and trained a NER model based on the BERT tagging model with the newly corpus. Which achieves an overall 82.09 F1 score on Mongolian Tourism Named Entity Recognition and lead to an absolute increase of +3.54 F1 score over the traditional CRF Named Entity Recognition method.

Supply Chain deals with fulfilling the customer request be it directly or indirectly. It involves forming a link between customers, warehouses, manufactures, retailers and suppliers. Customer experience is one factor that the company should keep in mind when deciding its supply chain network. Smart Logistics, in recent times, has a huge role to play in making the supply chain efficient and responsive. With the combination of logistics and technology, the transparency in the whole process would be increased which would lead to reduced turnaround time and ensuring safety, quality and privacy of the items delivered. This research paper aims to analyze the supply chain of food delivery business and based on those device strategies which ensure maximum participation of the customer at each stage in food delivery supported by feedback from over 120 frequent users of food delivery business from different age brackets. The entire research happens in a step-by-step manner in which the first part is based on understanding the industry, finding the key parameters and then collecting various survey opinions and responses to identify the issues faced during food delivery and how it affects the entire supply chain and lastly making a list of the key considered challenges and prioritizing them using Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

Recent technological eco-space has observed an exponential increase in the number of devices connected to the Internet. The data generated by these devices has reached astronomical figures. Due to this, there exists a need for managing and processing the big data, at the same time maintaining the reasonable latency. This requirement of today’s world in the field of Internet of things has given rise to technologies like fog computing, edge computing, mist computing, etc. This paper focuses on new technologies which are improvements of existing cloud computing. A computational analysis of fog computing is performed using iFogSim and cloudAnalyst simulator to carry out latency and cost comparisons between fog and cloud computing. As simulation results conclude fog has a lower latency of 159 ms, but at the same time, it has a higher total network implementation cost of $2.39, while the data transfer cost remains the same.

The changes in strategy, leadership approach, governance, services, technologies and almost every other aspect of business life make the banking/financial services industry a most interesting one to examine with the wisdom of hindsight. Lessons can be effectively learned in all these realms from past successes and mistakes in this sector. The recent Royal Commission and scandals such as the alleged 23 million breaches at Westpac reported in late 2019 make leadership, governance and strategy in the financial sector a very much live issue, with very many challenges to overcome.

In this chapter we note that leadership can be a daunting and challenging role and set of tasks, demanding a lot of individuals, but that it can also be very satisfying, when conducted well, because of the outcomes that it drives for individuals and organisations. While leadership roles are demanding on us, it is a natural progression for many to move towards and into partial or full leadership roles, and just like anything else, such work can be done to a great or to a lesser effect. To that end and purpose, we provide a total of twenty-one distinct advisory guidance elements for developing leaders to consider as elements of their journey and capability set. These range from analytic and technology oriented, to behavioural and people-oriented elements, all of which are necessary for a well-rounded leader to be able to affect.

Twitter has gained enough popularity nowadays and collecting people’s emotion, opinion, suggestion, feeling, knowledge and current market trends in the form of post on day-by-day basis from different countries, in multiple formats and languages; it is an absolute form of unstructured, rapidly growing million dollar worth data that is difficult to manage and process. This kind of data is mainly referred to as big data. The Hadoop ecosystem evolved around this problem space and offered effective management of this kind of data starting from capturing through processing till workflow management. This research is mainly aimed to provide an effective well-scalable framework to collect, process and analyze tweets using the Hadoop ecosystem. Here, Apache Flume is used to capture and store data in HDFS, Apache Pig and Apache Hive are used for data processing and analysis, and Apache Oozie is used for workflow management and task scheduling. This research also did the performance benchmarking over Hive and Pig on these data to find the recent trends, top influencers and top posts in various data categories. Experimental research concluded that Apache Pig outperformed over Apache Hive in terms of processing time while analytics results were same.

Following the testimonies of Shaimaire Sanni about the negative wanton use of artificial intelligence (AI) politicking approaches by the Vote-leave group during the 2016 Brexit referendum, the decision by Great Britain (GB) to leave the European Union (EU) had stirred up heated controversies about what would have really been the outcome of the Brexit deal if the Vote-leave group had not cheated with AI politicking systems. Hence, the act of cheating via this platform and the violation of Brexit spending regulations, human rights activists (HRA) like Sanni and Wylie believed, delegitimize the results of the votes obtained for Brexit and for UK’s institutions of democracy. Others argue that the allegations raised against the Brexit referendum process justify the agitations for a second Brexit referendum by a section of UK citizens. The Marxian alienation theory and Derrida’s critical and analytical method for evaluating qualitative data and arguments gathered on the subject matter of the paper were adopted, with the view to ascertaining the degree of AI politicking approaches that altered the results of UK’s Brexit referendum. Marilyn’s ex-post facto research method was also utilized for interrogating the integrity of UK’s democracy in the light of the allegations raised against it. The study observed that most of the allegations raised against UK’s Brexit referendum process had merits to their claims, thus justifying their request for a fresh referendum. A positive implementation of AI politicking methods from ethical perspectives was recommended against the current reckless methods adopted by political campaigners.

In this paper, we have proposed a watermarking system that is based on the spatial domain and is blind and robust in nature. This scheme is developed to withstand most of the image processing attacks. The watermark has been embedded in the cover image by modification of the DC coefficients calculated in the spatial domain. This method directly calculates DC coefficients in the spatial domain. The values of pixels can be changed/modified in the spatial domain in accordance with available watermark information. Since we have avoided the time-consuming transform operation, i.e., Discrete Cosine Transform, the computational efficiency is very high. For embedding a watermark bit, a particular image is disintegrated into 8 × 8 blocks, followed by further division of each block into two 4 × 4 blocks. After calculation of the DC coefficient of each 4 × 4 block, the watermark bit is embedded by modifying the DC values such that the DC coefficient of one block becomes greater than the other. The output results prove our proposed technique is highly robust to commonly occurring signal processing attacks. Experimental results obtained against numerous signal processing attacks are represented in terms of quality measuring parameters like PSNR, SSIM, and BER to check the efficiency and execution of our scheme.

An image feature, such as edges and interest points, provides rich information on the image content and plays an important role in the area of image processing. These correspond to local regions in the image and are fundamental in many applications in image analysis. Raw data are complex and difficult to process without extracting or selecting appropriate features in advance. Feature extraction, a data reduction technique, is the transformation of large input data into a low-dimensional feature vector. It lowers the computational cost and also helps in controlling the issue of dimensionality. There are different methods of exacting features from an image and these techniques have different domains of applications. In this paper, four widely used feature detection algorithms, Harris, SURF, FAST, and BRISK feature detection algorithms are compared in terms of accuracy and time complexity for extraction and matching of feature points correctly. For this purpose, different types of transformations are added to the original images for computing the evaluating parameters like the number of features detected, matched features, and execution time required by each algorithm. Experimental results show that SURF performs better than other feature extractions and matching algorithms in terms of accuracy and run time.

With the exploration of the Internet, social media platforms provide users to share their views toward various products, people, and topics. Nowadays, social media platforms have not limited their users to post or share only text but also images and videos to express their opinion or other social media activity. Multimodal sentiment analysis is an extension of sentiment analysis that is used to mine the heterogeneous type of unstructured data together. This paper gives a review of sentiment analysis and various studies contributed in the field of multimodal sentiment analysis and also discusses some important research challenges in the sentiment analysis of the social media data.

In data warehousing, view selection (VS) is an important aspect. Optimal VS needs to be materialized in order to minimize the overall data retrieval time. To support the same, performance metrics like memory constraints to save materialized views, query execution time, and query workloads needs to be addressed to reduce the overall retrieval time. As far as static view materialization (VM) is concerned, pre-computing strategies are required to execute the query workload prior to VM, but the approach is not scalable for small disk sizes. In the current era, the memory requirement is humongous to store pre-computed views in the materialized query table (MQT) that adds an overhead to view maintenance cost and disk sizes. To address the aforementioned issues, the authors propose a novel VM scheme DAMS. DAMS operates in three phases. In the first phase, the scheme chooses a materialized view in a dynamic and on-demand basis to reduce the query processing time. Then, in the second phase, a novel attribute selection algorithm is proposed based on association rule mining (ARM) technique in VS to address historical queries. It selects a candidate view from a pool of such views. As the number of queries is large, the proposed algorithm reduces the computational latency in fetching the view result. Finally, selected views are prioritized by grouping items as clusters set based on support and confidence metrics to speed up VM operations.

Paraphrase refers to the text which tells the same meanings but with different expressions. It is important in NLP as it deals with many applications such as information retrieval, information extraction, machine translation, query expansion, question answering, summarization and plagiarism. Paraphrase detection is to find that given two texts are semantically similar or not similar. Though paraphrase detection has wide literature, there is no proper algorithm for paraphrase detection in Punjabi language. A new paraphrase detection model for Punjabi language is developed in this paper. We use two deep learning methods to map sentences as vectors, and these vectors are further used to detect paraphrases. Despite other implementations of paraphrase detection, our model is simple and efficient to detect paraphrases. Qualitative and quantitative evaluations prove the efficiency of the model and can be applied to various NLP applications. The proposed model is trained on Quora’s question pair dataset which makes new directions for paraphrasing in Indian languages.

This paper is a review of enhanced techniques for detecting the multimodal fake news. It helps to develop an insight into the characterization of a news story with different content types and its influence among the readers. We review different techniques on machine learning and deep learning with its merits and demerits. The paper is concluded with the open research challenges that can assist the upcoming researchers.

In recent times, the reach and influence of social media have grown tremendously across the entire globe. The ease of access, simplicity, publicity and reach offered by giant social networking sites have come to hold immense value nowadays. However, this has led to the widespread use of fake accounts or programmed bots in order to inflate one’s social media popularity and further spread favourable content. Many recent studies have highlighted the impact of such bots in fields like advertising, commercial promotion and even elections. In this paper, we propose a method to detect bots on social networking sites and distinguish them from genuine user accounts by using a stacked learning approach whereby a convolutional neural network model is trained to feed forward to a machine learning model. This is achieved by using a supervised learning approach to build a layered classifier that makes predictions based on a user’s profile information, tweets and activity information from a dataset of Twitter users. Our paper also analyses the comparative performance of many machine learning models applied to this problem.

Extremely usage of smart wearable devices such as smartphones and smartwatches which contain various sensors for location detection such as Wi-Fi, LTE, GPS and motion detection such as accelerometer, it has become easier to obtain user mobility data. Today communication systems are becoming more popular due to the developments in communication technologies. There are various services provided which also help to access the data such as video, audio, images from which we can be used to grab the information or pattern of user mobility. The user mobility where user’s movements and locations can be predicted using various methods and algorithms. It can be predicted through data mining, machine learning, and deep learning algorithms where user’s data are fetched from the communication system. A comparative data mining model base on DBSCAN and RNN-LSTM was proposed for predicting the user’s future location-based information predicted from the last locations reported. Mobility prediction based on the transition matrix prediction is done from cell to cell and calculated with the help of the previous inter-cell movement.

This chapter expands on previous arguments by analyzing discourses on the alleged failure of multiculturalism in Europe and the increasing culturalization of mainstream politics. It argues that this not only presents an integration paradox but, in a much more fundamental sense, also entails a redefinition of the basis of European liberal democracy. In a sustained theoretical reflection, the chapter argues against conceptions of liberalism that aim to invisibilize problems of cultural accommodation within a sanitized discourse of individual rights. Its core purpose thus concerns—on a theoretical level—a way of turning the experiences of pervasive pluralism and large-scale immigration into emancipatory sources of liberal democracy rather than into driving forces of its erosion.

Exploring user attitudes and behaviors within the domain of interests helps the user experience team to match the user with a deeper understanding. The mapping process also reveals any gap in existing user data. Design thinking is the ground-breaking and cooperative approach to problem-solving that puts the user first to make user-centered products and services. There are many various design thinking activities that use to generate a thoughtful of the users or customer, including the conception of personas. This paper revisits the concept of persona and draws the connection of using empathy map to build persona within the design thinking process. Also showing the benefit of empathizing method to construct the effective persona. This can be used for the benefit in Human Computer Interaction(HCI) designing processes or marketing analysis.

The increasing popularity of e-commerce websites and online review platforms has unfortunately led to the advent of review spammers. This has, in turn, led to many problems, both in business and in academia. One of the major challenges in this field is the annotation of deceptive reviews. To date, different approaches have been employed in the creation of a labelled dataset for classification tasks. Many of these works follow a general approach and do not focus on any particular property of deceptive reviews. We believe that a fine-grained approach would be more suitable for such a complex problem. This paper focuses on a single property of deceptive reviews; the out-of-context property. We first find the minimum length of review required for obtaining coherent topics. We then propose a methodology for scoring and labelling the reviews and evaluate it by training different classifiers. We obtain an F-measure of 93.64 using labelled reviews obtained through the proposed methodology.

Dieses Kapitel vermittelt Ihnen, wie Sie Ihren Arbeitsalltag mit Hilfe von SAM neu gestalten können – nämlich zunehmend systematisch, agil und multimedial. Die drei Säulen mit den gleichnamigen Anfangsbuchstaben stehen (1) für die wichtigsten inhaltlichen Strukturen und Verfahren. Dabei spielt auch das sichere Beherrschen von Soft Skills eine große Rolle. Was das genau heißt, sehen Sie anhand zahlreicher Beispiele und praktischer Hilfen. Vollziehen Sie (2) agile Dienstleistungskonzepte anhand eines großen praktischen Erfolgsfalls nach. Dabei wird auch ihr rechtliches und tatsächliches Verständnis von Homeoffice- und Mobile Office-Regelungen geschärft. Schließlich vergrößert die Lektüre (3) Ihr Know-how zu Kommunikationskanälen in aller analogen und digitalen Vielfalt. Dabei lernen Sie sowohl die zentralen juristischen als auch die wichtigsten technischen Besonderheiten kennen.

In the last chapter, we learned about BERT and its usage in the design of a question answering system. This chapter discusses how BERT can be used for implementation of other NLP tasks such as text classification, named entity recognition, language translation, and more.

This chapter is focused on analysing the processes and elements that have shaped the particular neopatrimonial and authoritarian nature of the Uzbek state, from its origins and early consolidation under Karimov to the transformations during Mirziyoyev’s presidency. These factors have predominantly developed in the domestic sphere, due to the high degree of autonomy from outside influence of Uzbek authorities and elite networks, compared to other Central Asian cases, such as Kyrgyzstan, Tajikistan or Turkmenistan. This tendency may vary in the future, if the development strategy of “openness” started by President Mirziyoyev is finally consolidated.

In 2019, Kazakhstan’s president Nursultan Nazarbayev surprised the world by voluntarily stepping down after almost thirty years in power to leave space for “a new generation of leaders.” Kazakhstan has become the success story of post-communist development in the region. Investors, domestic elites, and foreign leaders have been praising the stability of Nazarbayev’s neopatrimonial regime. Nazarbayev, however, is the first Central Asian leader who chose to step down from the presidency through a political tandem with the chairman of the Senate and second in line for the presidency, Kassym-Jomart Tokayev. Despite the fact that Tokayev finds himself in a secondary role in Kazakhstan’s political system, he has taken some steps toward changing his image and has shown some controversial signs of liberalization. This chapter discusses the turbulent relationship between political elites and the opposition in Kazakhstan, following the analytical model of the Sociology of Power. It first presents the elites that control Kazakhstan, the competition that these elites face from abroad, and the most significant groups and leaders that can mobilize popular discontent. The focus then turns on the strategies that Kazakh elites used to maintain power and the prospects of Kazakhstan’s transition.

Where is local self-government heading in the future? Among trends identified is firstly an intensification of multilevel, intermunicipal, and cross-border governance. In the future even more of cooperation and coordination among different political and administrative levels will be required. Territorial boundaries have become increasingly incongruent with functional public activities. Secondly, the innovative potential of introducing markets as templates for organisational reform has reached its end. Future reforms will most likely try to adapt market reforms to local public contexts, or even reverse the development. Finally, a tightening of state steering and an increased dependence on state funding to uphold local services is expected. Waves of amalgamations might slow down this process but they will not make financial problems disappear completely.

Tomas Bergström discusses, with examples mainly from Sweden, the future of party-based local democracy. Could local democratic systems change as conditions change and remain vigorous? Long-term trends present a rather dystopian picture that seems to result in reduced discretion and depoliticisation. Changes that has taken place like globalisation, marketisation, the impact of social media and new roles for courts challenge local politicians’ chances of governing local matters. Decisions are taken at other levels, by other actors than elected politicians or in complex networks involving a number of partners and stakeholders. Historically local governments have been able to adjust to new conditions. Whether this is the case also now remains to be seen.

The growth of Online Family Dispute Resolution (OFDR) means that consumers are now presented with a range of options on the market to suit their needs. With the intention of these services to optimise effectiveness and efficiency for their users, it is paramount that robust evidence be demonstrated for their quality to support their preferential use when compared to other forms of dispute resolution service delivery. The literature review presented in this chapter was conducted to scope the current research and practice evidence for online dispute resolution in family law as relating to child custody issues. The use of OFDR services in both Australian and international contexts was investigated across a range of electronic sources since 2011. Of those programs located by the review, it was evident that while more methodologically rigorous research is required, preliminary evidence shows support for OFDR effectiveness in reaching desirable and fair outcomes. The considerations for selecting technologically-enhanced services are discussed, as are the avenues for future research and directions to further develop OFDR as a viable option for informal conflict resolution. This chapter demonstrates how knowing the literature helps to inform future OFDR development and enhance service delivery.

This book has presented the case for the value of integrating technologies into the family law arena particularly within Australian contexts but with clear implications for family dispute resolution (FDR) services worldwide. Online dispute resolution (ODR) has already experienced success across a wide range of other conflicts, with preliminary evidence in the growing field of online family dispute resolution (OFDR) showing favourable outcomes for separating parents. The research presented in this book supports arguments that OFDR increases access to quality FDR services which in turn facilitates child-centered decision-making. This chapter will summarise the lessons learned to-date to inform recommendations for future OFDR program design and improvement. Both ODR and OFDR are relatively young developments in Australia, so the potential of these advanced technologies and their capabilities is yet unknown. Continued rigorous research into existing and future OFDR programs will further improve the field and the outcomes for families, an endeavour that will take the collaboration of many different stakeholders and a commitment to ongoing learning and future-focused change.

The chapter describes the origin, goals and the main figures of Domain Committee on Information Technology in Disaster Risk Reduction (DCITDRR), established by the International Federation for Information Processing (IFIP). Key activity, such as international conferences organized by DCITDRR, and some of the scientific research projects of DCITDRR members are presented.

This chapter focuses on group discussion sessions targeting the Priority Areas of the Sendai Framework for Disaster Risk Reduction 2015–2030. Day one group discussion session efforts were on Priority Area One—Understanding Disaster Risks; and Day two emphasis was on Priority Areas 2, 3 and 4.

Artificial intelligence has become a new engine for economic growth and as the central driving force of the new round of industrial reforms, artificial intelligence will further discharge the energy accumulated from prior technological revolutions and industrial alterations by generating new powerful engines to modernize economic activities such as production, distribution, exchange, and consumption. The decentralized nature of blockchain generates, the new concept of a token economy in which the community’s revenue is allocated to the actual content producers and service users who generate value. In addition, Blockchain is a key technology that enables new protocols for the establishment of a token economy in the future, leading to a new economic paradigm. Digital technologies are now turning the world upside down and so an ongoing series of technological developments have transformed economic and social life. The integration of AI agents into society has led to a different manner in which persons interact with each other, along with a new kind of direct interaction presented with AI agents, which are increasingly posed in society.

Risk is a tool which makes possible the decision-maker to get knowledge about the event with destructive effects and so, the decision-maker via the analysis of risk makes the event more certain and obtaining control on it. Moreover, risk is the net negative influence of the exercise of vulnerability, regarding both the prospect and the effect of occurrence. Risk management is the procedure of identifying risk, assessing risk, and taking steps to moderate risk to a tolerable point. Furthermore, Risk sharing or risk controlling are central justifications for joining strategic alliances. Credit risk surfaces from the prospective that one participant to a financial tool is triggering a financial loss for the other participant by neglecting to discharge an obligation. Managing risk is one of the key objectives of companies operating globally and managers normally correlate risk with negative result.

Corporate governance refers to the relationships among the different internal and external stakeholders implicated with the governance processes planned to assist a corporation in order to accomplish its objectives. DLT adoption by market participants will involve which means that there is a likelihood that new kinds of corporation stakeholders will appear such as the token holders. Hence, these new players will lead to alterations in the securities’ issuance and trading, in the shareholder’s involvement, but also to a reinforcement of the rights awarded to the different corporation stakeholders and so a new role will be recognized to corporate stakeholders. Public blockchain systems are “trust-minimized,” but “trust-shifting”—which indicates the need to trust in others than the officers and directors of a bona fide corporation and so in these systems that operate money, smart contracts, and possibly many other critical human practices which means that people continue to lead and make vital decisions on behalf of others.

The new era of information technologies is referring to the globalization of communication. The quick decrease of the communication costs enhanced the dealings among countries and is a vital foundation for the structure of a stronger universal civil society. In today’s technology-driven world, industry standardization, device interoperability, and product compatibility have turned out to be vital to advancing innovation and competition. The technologies and virtual places that represent cyberspace have been assimilated into the lives of people who accept the Internet as a tool for pursuing their common, real-world needs. E-government brings the government closer to citizens, defeating the barriers of bureaucracy, reducing corruption, and making decision-makers more reactive to people’s needs, which means that e-services of e-government are characterized by greater efficiency and transparency.

Law can formally be considered as an institutionalization of practical discourse on social norms, and so modern law in Western civilizations is positive by articulating the will of a sovereign lawgiver, legalistic by applying to deviations from norms and formal. Public international law portrays itself as an instrument of universal moral values, of human rights, and of justice. There is a shift from international law to law and globalization providing a new incentive for erasing the artificial boundary between public and private in international law. It is characteristic that modern societies are far more interconnected than societies have ever been in the past, and so with the advances of technology and infrastructure, networks have quickly become an integral part of humans’ lives. AAI technological advance unavoidably is altering human and social behaviors demanding an adaptation of existing norms or the creation of specific rules if the law in force proves inadequate or unproductive. Essentially, AAI will be a cross-cutting happening necessitating not only the establishment of specific standards but also the reconsidering of the feasibility and effectiveness of preexisting rules. Zekos considers that at the verge of humanity losing earth’s control, there will be a war of humans against AAI machines by immobilizing the AAI intelligence and arriving at zero point for a restart.

It seems that advanced technology and Al acts and thinks like humans. AI is an exceptional information technology demanding the event of a machine that reacts and works as a mind of the human. Moreover, the upcoming of AAI systems lead to global governance challenging the conventional international law. It is worth mentioning here that AAI systems generate a clear-cut need for new sui generis rules to cope with new AAI situations or types of conduct. AAI will ignite morally problematic or politically or strategically disruptive forms of conduct by controlling the global population, deploying fully autonomous weapons forming cyber-warfare systems establishing stability in AAI global society via the AAI. In conclusion, Al has to be utilized by people for the good of the whole society and not being a weaponry on the hands of an elite to conquer earth against any costs of human life and prosperity.

Happiness is a concept that changes according to individuals. However, in general terms, happiness can be expressed as an overall positive assessment of one’s quality of life. The branch of economics makes happiness measurements by looking at happiness from an economic point of view and examines their relations with economic factors. Happiness economy, on the other hand, examines which factors increase or decrease the quality of welfare and life and makes inferences about this issue. The aim of this study is to examine work done related to the happiness economy and the change in happiness in detail in Turkey and is to interpret in detail the current data on this subject. For data on Turkey published regularly since 2003, “TSI Life Satisfaction Survey” results were used. The study also mentions the happiness measurement techniques and contents made today and gives the latest happiness researches of all countries in the world. Countries happiness data are compiled from the last publication of the “World Happiness Index.” The study focuses on the relationship of happiness with variables such as income, employment, health, and social status, which are the determinants of happiness in the economy, and their effects on happiness.

The aim of the present paper is to gain a deeper understanding of the essence of the “Future of work” by exploring simultaneously its major drivers and their impact on the job market and employment on European level in the long run. The data used are based on the research of numerous international organizations, European Union institutions, and bodies, as well as on analytical data and expertise of reputable business consulting companies. The methodology includes qualitative research, including data analysis, comparative analysis, inductive and deductive approach, and others. This type of research helps to explore how and why the phenomenon “Future of work” occurred, what it represents and what the prospects for its development are. The main drivers of this phenomenon are analyzed as follows: globalization, digitalization, and demographic change. The paper explores and summarizes the expected economic and social effects of these three factors on the labor market in the EU. The main findings conclude that the “Future of work” is an interdisciplinary phenomenon covering the current and expected trends on the world labor market, provoked by the dynamic technological development and penetration of artificial intelligence technologies in the economic and business practice, including job automation (job loss and job creation), rising skills and qualification requirements, a big change in employment occupations, and rising diversity in working arrangements. Legislative, business-oriented, and educational actions on all levels are urgently required to face these new challenges successfully.

In this paper, we study how local interactions in suitably structured social networks give rise to globally emergent states and observable patterns. An example of such states and patterns is the emergence of Panopticon-like structures that possess global surveillance properties. Our methodology is based on elements of game theory and innovation diffusion graph processes modeling social network local interactions. We provide an example of a simple social network structure in which collective actions induce the emergence of specific behaviors due to the effects of the local dynamics inherent in strongly interconnected individuals. Our work provides a framework for studying and explaining how specific social interaction patterns produce already observable global social patterns.

Al technologies affect the center of private autonomy and its limits, the notion of a contract and its interpretation, the equilibrium of parties’ interests, the structure and means of enforcement, the effectiveness of legal and contractual remedies, and the vital attributes of the legal system of effectiveness, fairness, impartiality, and predictability. The increasing global investments in blockchain technology justify a progressive regulatory adaptation to the altering materiality and so, civil liability and the insurance sector are required to amend and govern an ever-more pressing techno-economic evolution. It is worth noting that adapting existing rules to deal with the technology will need an understanding of the various manners robots and humans respond to legal rules. A robot cannot make an instinctive judgment about the value of a human life. It is argued that the automation of legal services is a manner to enhance access to justice, diminish legal costs, and upgrade the rule of law, which means that these improvements are a democratization of law. There is a shifting role of artificial intelligence in the legal course.

In online interactive platform, text analysis has greatly changed people's communication, thinking, and promoted the explosive growth of user-generated information. A large number of texts generated by users have become one of the most representative data sources of big data in recent years. Mining and analyzing user-generated information has become essential part on research of social development. The sentiment analysis on social media text as an information processing technology for analyzing, processing, summarizing and reasoning subjective texts with emotions has received extensive attention in academia and industry in recent years, and has been used among many areas of social media and many applications. The traditional text sentiment analysis research work mainly focuses on analyzing emotions from texts, but ignores the individualized differences of users in emotional expression, thus affecting the quality of analysis results. To solve the problems, this paper is about solving the problem of personalized sentiment analysis of social media texts. Considering the wide application of BP neural network technology in social media was proposed to solve the possible challenges of social media text personalized sentiment analysis.

The outbreak of the COVID-19 pandemic has a multi-faceted impact on the mobility of travelers. Current research has not yet explained the internal mechanisms of travelers’ mobility changes during the pandemic. The Bayesian network is considered to be an effective method to describe the causality between the factors and output of a system. Thus, this paper established a Bayesian network model to analyze the impact of COVID-19 on Chinese travelers’ mobility decision–making processes. The model for the traveler mobility decision-making process is built on both a qualitative and quantitative analysis of travelers’ self-narration articles. Results show that official information, traffic information, family structure, and social interaction networks are the key factors affecting Chinese travelers’ mobility.

The paper presents an exploratory research focused on the themes concerning Chinese Outbound Tourism to Switzerland in the period from January 2019 to June 2020 including the Covid-19 outbreak. It analyses news media articles from Swiss-German print media covering tourism coming from China, including a visit by 12’000 Chinese travelers – an event extensively covered within Switzerland due to its exceptional number – up to recent times in which non-European tourists are almost absent from the country. The research aims at identifying the main themes being voiced in newspaper articles. It also tackles the themes mentioned in user-generated comments on Facebook on the same articles.

In the last decade, Information and Communication Technologies have revolutionized the tourism and hospitality sector. One of the latest innovations shaping new dynamics and fostering a remarkable behavioral change in the interaction between the service provider and the tourist is the employment of increasingly sophisticated chatbots. This work analyzes the most recent systems presented in the literature (since 2016) investigated via 12 research questions. The often appreciated quick evolution of such solutions is the primary outcome. However, such technological and financial fast-pace requires continuous investments, upskilling, and system innovation to tackle the eTourism challenges, which are shifting towards new dimensions.

The purpose of the study is to investigate whether cultural differences are reflected in how destinations present themselves online by performing hyperlink network analysis of their official DMOs websites. The study examines whether variance in online presentation can be explained using well established theories on culture. To this end, hyperlink data were collected from three official tourism websites: Korea Tourism Organization (KTO) of South Korea, Brand USA of United States, and German National Tourist Board (GNTB) of Germany. The results show that the three hyperlink networks exhibit differences in size and structural properties. The information network of KTO tends to reflect collectivism, while those of Brand USA and GNTB reflect individualism. Blockmodeling analysis provides the grounds for further statistical approach.

This paper presents a conceptual framework “sitesharing” for understanding touristic consumption within the smart tourism paradigm. Smart tourism considers the use of ICTs as beneficial and essential to the future of tourism. However, the integration of technological intermediaries with the sphere of tourism bears investigation in terms of the wider effects on tourism processes. Taking an interdisciplinary stance, the paper utilizes an internet studies perspective in order to examine the political, social, and cultural implications of the integration of ICTs within tourism. Through the exploration of three key metaphors drawn from across the fields of study: performance, place, and sharing; the paper considers how ICTs influence tourists’ consumption, telling, and experiencing of tourism. The framework of sitesharing argues that sharing, rather than seeing, becomes the requisite practice of tourists with concomitant changes in the form of tourist practice and the shape of tourist places. From the discussion, four emergent dimensions of sitesharing are presented with the intention of informing future tourism research.

Similarities may be seen in the development of tourism in Japan and Switzerland during the nineteenth and twentieth centuries, especially in terms of the origins and purpose of their respective national tourism offices. In the twenty-first century, however, fundamental differences became evident. During the first decades of the twenty-first century, Switzerland, that had been quick to see the opportunities of e-tourism, was less dynamic in response to the fourth and fifth industrial revolutions, whereas the opposite happened in Japan. Switzerland as with Austria and Germany, adopted a traditional concept of DMO’s that was location-base and limited regionally by administrative boundaries. The Information and Communication Technologies (ICT) development after Web1.0 and the emergence of mobile applications have challenged this concept. A more contemporary view is based more on network travel and visitor flows rather than physical territory. The Japan Central government decided to adopt the western DMO concept as regional tourism policy, but relatively late in 2016.The aim of this innovative research project is to analyze the adoption/implementation of the new concept of DMO’s focusing on Switzerland and Japan. For Switzerland, the main barrier is the scarcity of data given the slower uptake of the technology emanating from the fourth and fifth industrial revolutions. In Japan, the situation may be seen to be inverted, given the country’s proclivity to adopt the advantages from the latest industrial revolution. This may mean that Japan could leapfrog the traditional DMO concept. This research presents the Bass’ analysis of DMO’s websites as a proxy of DMO concepts – traditional or new generation.

This research investigates destination imagery of Switzerland as a travel destination. This research first conducted survey and content analysis to identify 23 unique statements reflecting travel in Switzerland. Through an online survey, this research collected 399 responses from French and Italian respondents. Based on the comparisons of association strength and association valence of every statement to the aggregated association strength and association valence, this research developed the Destination Imagery Diagnosis model. The results show that, overall, French and Italian respondents have strong and positive associations to statements related to Switzerland’s nature and opportunities for outdoor activities. Furthermore, respondents rated “Healthy lifestyle” and “Welcoming and friendly” positively but the associations to Switzerland were weaker. This research also identified marketing opportunities specifically for French and Italian respondents. The Destination Imagery Diagnosis Model serves as a new tool to compare destination imageries between markets or keep track of changes of destination imagery.

Even though social media is one of the most significant marketing tools in tourism, the measurement of its value is still developing. Assessing return-on-investment on social media marketing is challenging. Thus, destination marketing organizations (DMOs) are nonetheless pouring money and time in social media marketing without being aware of the results. In this study, we seek to understand what DMOs are measuring in social media marketing that they do and why. The qualitative data was gathered via semi-structured interviews among eight representatives of Finnish DMOs. The interview responses were analyzed with a theory-guided content analysis method. The results demonstrate that even though the goals for social media presence are clear, the actions taken are more of an experimental nature and undocumented. Only the basic metrics that the platforms automatically provide are used and the evaluation of financial value is difficult. However, social media marketing creates value beyond financial value. Non-measurable data like customer emotions and opinions in various channels are considered as important especially to understand customer engagement. Even though the evaluation of financial value is challenging the total value of social media marketing is considered extremely valuable. Social media marketing is utilized in decision-making by top management especially with the help of measurable data. In addition to this, non-measurable insights are utilized in product development and marketing planning.

The global tourism industry has been devastated by the COVID-19 pandemic due to strict travel restrictions imposed by most countries. In order to achieve a swift post-pandemic recovery, it is important to understand what psychological obstacles people would face when making travel decisions. Building upon the dual-route theory of information processing, this study examined and compared how the perceived risk of COVID-19 would affect people’s travel intentions in the Japanese city of Sapporo and the Chinese city of Wuhan through two rounds of data collection. While both cities were hit hard by the COVID-19 pandemic at an early stage, the cumulative numbers of confirmed human cases and the levels of intervention adopted were largely different. Results from the present study showed that risk perception of COVID-19 had a negative effect on people’s travel intentions in Sapporo. However, no significant effect of COVID-19 perception could be observed in post-lockdown Wuhan. Meanwhile, although the dual-route structure of information processing was obtained in Sapporo and post-lockdown Wuhan, neither routes seemed to predict the perceived risk of COVID-19 in Wuhan when lockdown restrictions were still in place. Several theoretical and practical implications concerning the results are discussed in this study.

The pandemic outbreak of COVID-19 in 2020 has profoundly affected the global leisure and tourism industry, with international travel bans affecting over 90% of the world’s population. Widespread restrictions on community mobility have resulted in a projected decline of international tourism arrivals up to 30%. The rapid development of Virtual Reality (VR) and its effectiveness in the simulation of real-life experiences provides an opportunity for virtual holiday making especially when actual travel is not possible. Based on a quantitative study with 193 participants, the role of VR as a substitute for physical travel during the pandemic outbreak of COVID-19 was examined, more specifically by looking at the relationship between perceived risk to travel and technological acceptance of VR. The findings suggest that tourists use VR as a travel substitute during and even after a pandemic. However, perceived risk does not play a significant role when it comes to using VR.

Governments across the world have imposed strict rules on social distancing to curb the spread of Covid-19. In particular, restaurants have been impacted by government-mandated lockdowns. This study adopts a mixed methods approach to explore how Finnish high-profile restaurants used Instagram as a means for service innovation and diffusion during nine weeks of government-mandated lockdown. Comparatively analysing 1,119 Instagram posts across two time-stamps (2019 and 2020) and across 45 restaurants, as well as conducting five semi-structured interviews with restaurant managers, it is found that while the overall number of Instagram posts and likes on posts stayed relatively similar to the year prior, the number of comments increased significantly, suggesting a move towards a more didactic and dyadic form of Instagram communication. In addition, four digital service innovation strategies are identified: launching new service offerings and introducing new elements to existing service offerings, fostering social relationship with customers, exploring novel streams of revenue, and reinvigorating the brand’s image. Implications to service innovation theory and practice are discussed, along with suggestions for future research.

Tourism is a lucrative business, and Swiss hotels rely heavily on international clientele to book their rooms. The Coronavirus pandemic has halted travel and hotel stays from March to June 2020. Based on Situational Crisis Communication Theory (SCCT), this paper investigates the messages Swiss hotels have posted on their official websites and Facebook pages to reassure guests that it is safe to book rooms in Switzerland again. The findings from 73 independent 4 and 5-star hotels show that most hotels did not publish messages regarding the Coronavirus or the measures they have taken; instead, the hotels posted positive messages about reopening their rooms and services. Official hotel websites emphasized deals and offers while the Facebook pages concentrated on enthusiastic ‘welcome back’ messages. The findings presented here contribute to the literature by offering the first results of a larger project on communication during the de-confinement stage of a pandemic.

Ongoing travel information search remains under-examined in general, and specifically in terms of social media use. Understanding how visual social media platforms inspire travel dreams is increasingly pertinent as visual contents gain in importance. This is especially relevant when travel is restricted, such as during the COVID-19 pandemic. Pinterest seems to be ideally suited for supporting ongoing search but has been rarely used as a data source in e-tourism research. This paper uses a netnographic approach to explore travel-related Pinterest data. From a methodological perspective, it finds that the platform is suitable for informing ongoing travel information search research but points to potential methodological challenges. As a theoretical contribution, it highlights the popularity of capturing travel dreams through Pinterest boards and illustrates the affective labor users put into their collections of travel dreams. The paper concludes with implications for tourism marketing and recommender system design.

Instagram has been an emerging platform for tourists to share their experiences and connect with other users in the multiphasic travel stages. Despite the huge number of photographs shared on Instagram on a daily basis, it remains ambiguous regarding the underlying motives of tourists’ posting behaviour. Thus, this study aims to conceptualise a framework based on the internal and external triggers of sharing travel photographs through a mix methods design involving diary studies and questionnaires. By conducting a path analysis, this study presents and validates a theoretical model including various motivational factors; namely enjoyment, self-esteem, recognition, interests, social norms, goals, social ties, social status and prestige, self-efficiency, outcome expectations and memorabilia. Meanwhile, this research clusters young techsavvy tourists into four distinct segments based on their behaviour of using Instagram while traveling. By bridging motivational theories, social psychology, and social media in the context of tourism, this research extends literature related to user-generated content and Instagram. Practically, this research allows marketers to optimise the effectiveness of marketing strategies based on the characteristics of tourists and their behaviour on social media platforms.

As a result of travel activities, overtourism has become a global issue. Even after the COVID-19 pandemic, the topic of overtourism would benefit localized overcrowding as a new occurrence in the tourism industry. Since there is no specific measurement to evaluate tourist experiences at crowded attractions, this study aims to explore the perception and feelings of tourists when they visit popular and crowded attractions through topic modeling and sentiment analysis based on TripAdvisor online reviews as of the end of 2019. By investigating the top 10 attractions in Paris, the results present 24 topics frequently discussed by tourists. Examples of some topics related to overtourism are safety, service, queuing, and social interaction. Specifically, tourists felt the most negative towards safety and security among all the identified topics. By bridging overtourism, text analytics, and user-generated-content, this study contributes to the field of tourist experiences and crowd management.

The study facilitates digital nomadism for tourism research and recognizes a unique product offer on the market: the combined coworking and coliving space in compelling or exotic destinations. The aim of the study is to explore the experience of coworking and coliving by digital nomads and identify valuable elements. Qualitative interview data are used to analyse combined coworking and coliving space environments from the perspective of digital nomad tourists. A better understanding of digital nomad preferences may help destinations and business owners to attract digital nomads during and after the pandemic. The study’s findings, perceived advantages and disadvantages of coworking and coliving spaces, may serve as a guideline for targeting digital nomads.

Travelling by land is a phenomenon that utilizes different surface transport modes, such as trains, buses, bicycles etc. The slow travel contributes also to the concerns about ecological footprint and climate change derived from air travel. Slow travel aims to encourage individuals to travel to their destinations more slowly, stay for a longer period in the chosen destination, and travel less. For slow travellers, travelling to the destination is a significant part of the travel experience. The qualitative research aimed to understand the phenomena of travelling by land and the tourist experience holistically using a netnographic approach. The data was collected from the Finnish Facebook -group, Maata pitkin matkustavat. (Those who travel by land) in January 2020. The data consisted of 185 posts and their comments. The goal of the data analysis was to understand the role of consumer value in the slow travel experience. The research findings show the importance of minimizing travel time and the costs of travelling by land. Also, leisure time, and “having fun” are valued in travelling by land experience. Thus, self-oriented, active value components, Efficiency, and Play, were most applicable in the collected data set. These findings help us to understand slow travel as a tourism experience better and provide important insights into the requirements to develop consumer-centric slow travel for sustainable development in the future.

With advances in technology affordances, contents generated by individual tourists in the tourism context has become an influential source of tourism information besides contents channeled by traditional mass media such as newspapers and broadcasts. Specifically, Meme Tourism (i.e., meme phenomenon in tourism) becomes one of the biggest trends in imitating and transforming/evolving tourism contents online, which is a byproduct of participatory culture that use text and visual images as means of user-generated communications in online communities through the exchange, distribution, and transactions. Understanding the emerging phenomena of meme in tourism would provide insights on tourists’ desires and behaviors in modern traveling. This study conceptualizes three major perspectives in tourism; 1) media-induced tourism, 2) user-generated content, and 3) social media activities, reflecting meme phenomena in tourism. Given the foundation provided, this study calls for a new stream of study in tourism that examines desire, motivation, and behavior of tourists in technology-enabled modern travel culture.

Image-based social media such as Instagram is actively used as a tourism marketing channel that provides information regarding tourist destinations. Recognizing the importance of viewers’ responses, this study investigated the relationship between viewers’ responsive behavior and the characteristics of texts and images posted on Instagram. The results of multiple regression analysis showed that certain emotional expressions in hashtags and images that include people are positively associated with the number of likes and comments. This study provides insights into social media utilization strategies and post-marketing strategies that are helpful for DMO (Destination Marketing Organization).

Tourism and hospitality crises that are extensively discussed online are damaging to organizational image and reputation; therefore, choosing effective response strategies is of paramount importance for service providers. The online discussions data from six hospitality and tourism related crises were used to test which crisis and media coverage characteristics significantly affected the public’s emotional and behavioral reactions to crises. With reference to the attribution theory and the situational crisis communication theory, this study identified the potentially influential crisis characteristics, hypothesized their relationship with variables describing consumer reactions to crises, and then tested those relationships in a series of ANOVA and hierarchical regression analyses. Results indicated that the locus of control, crisis stability, attribution of organizational responsibility, and organizational response strategy affected the public’s cognitive and emotional responses to crises most strongly. The attractiveness and goodwill of media sources also had an effect, as well as the quality and fairness of messages. This study makes a methodological contribution to tourism research by training machine-learning classifiers prior to conducting hypothesis testing. Identifying the most influential factors affecting the public’s response to crises can serve as guidelines for tourism and hospitality organizations in monitoring the spread of online crisis discussions and developing the most appropriate response in order to minimize consumers’ negative emotions that affect online and off-line behavior toward the organization and its brand.

National parks attract millions of tourists to enjoy the beauty of nature. The opinions and feelings expressed by tourists in their reviews through social media significantly impact other visitors’ tourism-related decisions. Notably, tourists from different countries visiting the same park may express different sentiments and post different experiences. It is not clear if those differences could be attributed to the differences in sentiment analysis software for different languages, or they reflect existing variability in culturally defined tourists’ sentiments. To address this question, this study analyzed 27,177 TripAdvisor Grand Canyon, US reviews from visitors arriving from ten different countries with the goal of identification of sentiment differences. We found that while all reviews tend to be positive, there are significant regional differences with European and Japanese tourists routinely expressing lesser satisfaction from their visit. We also found differences in the sentiment expressed in different regions of the same country, such as the north and south of Italy. Overall, we suggest that social media reflects the real differences in the sentiment of visitors coming from different origins.

Social media data has been rapidly applied as alternative data source for tourism statistics and measurement in recent years due to its availability, easy collection, good spatial coverage at multiple scales, and rich content. However, frequent criticism towards the social media is the bias towards the population of social media users leading to unknown representativeness of the entire population. The purpose of this study is to cross-validate the reliability and validity of visitation pattern of tourist destinations retrieved from the social media using alternative independent data sources. The primary social media data is TripAdvisor reviews of Florida attraction points, restaurants, and hotels. The inferred visitation pattern was validated against two independent datasets: cellphone tracking data and official visitor surveys. The validity was explored in tourist origins, destinations, and travel flows. Repetitively, travel patterns inferred from the social media were found strongly correlated to those from cellphone tracking and surveys. The visitation data obtained from social media was concluded to be reliable and representative.

The personalisation-privacy paradox demonstrates a two-fold effect of tourists’ awareness about personalisation on their experience. Compulsory personal data agreements under the GDPR and similar legislation acts raise tourists’ concerns regarding privacy and security. The role of tourist awareness about the value of data-driven personalisation in their co-creation behaviour remains underexplored. This paper applies an exploratory experiment methodology to identify the effects of information about personalisation on tourists’ experience with travel information websites. It triangulates the data from eye-tracking and self-report techniques, to compare the co-creating behaviour of respondents who have or have not been informed about the value of personalisation. The study demonstrates the presence of a personalisation-privacy paradox. It further reveals that awareness about data-driven personalisation motivates tourists to reinforce value co-creation by ensuring the accuracy of information filtering. The study advances our understanding of tourist digital behaviour and provides insights for the design of personalised information services.

In the future, artificial intelligence (AI) is likely to substantially change both the tourism industry and tourist behavior. At present, research on artificial intelligence and tourism is receiving widespread attention, but most of them focus on a certain subject or a specific aspect of the tourism industry. For example, artificial intelligence influences the behavior of tourists and tourism enterprises. The analysis of the impact of artificial intelligence on the tourism industry as a system is still insufficient. Therefore, this research proposes a multi-dimensional framework from an industry perspective based on the existing definition of artificial intelligence. The framework involves three aspects: the level of intelligence, task types, and whether artificial intelligence is embedded in robots. The authors use a large number of Chinese practice cases to investigate how AI affects the tourism industry, then put forward a research agenda to analyze how destination government, tourism enterprises and tourist experience will change in the future. Finally, they highlight important issues related to privacy, prejudice and ethics.

The increasing implementation of digital technologies in organizations such as social media platforms is fundamentally transforming the nature of services encounters [1, 2], not least in the hospitality industry. This causes new ways of working for hotel employees, causing disruption in service routines and work tasks. There are few qualitative studies that are focusing on the hospitality industry and technostress. The present study focus on technostress among employees in an international hotel chain. Data have been collected in eight European countries over a period of seven years. The Person-Technology fit model is used in order to identify and analyze stressors and strains deriving from social media use. The results indicate that techno stressors such as work overload, work-life conflict, and changing algorithms creates negative stressors. The study makes a theoretical contribution to technostress research in the Information Systems research as well as the hospitality research field by uncovering negative stressors and strains created over time.

The COVID-19 pandemic has had a destructive effect on the tourism sector, especially on tourists’ fears and risk perceptions, and is likely to have a lasting impact on their intention to travel. Governments and businesses worldwide looking to revive and revamp their tourism sector, therefore, must first develop a critical understanding of tourist concerns starting from the dreaming/planning phase to booking, travel, stay, and experiencing. This formed the motivation of this study, which empirically examines the tourist sentiments and concerns across the tourism supply chain. Natural Language Processing (NLP) using sentiment analysis and Latent Dirichlet Allocation (LDA) approach was applied to analyze the semi-structured survey data collected from 72 respondents. Practitioners and policymakers could use the study findings to enable various support mechanisms for restoring tourist confidence and help them adjust to the’new normal.’

As digitization converges with globalization, industries across the world establish new standards, platforms and audience engagement methods to delight consumers adjusting to CV19’s virtual space. Within the Tourism and Hospitality industry, gamification provides the events and meetings sector an opportunity to implement hybrid events at a level unseen before. Esports is the newest standard of gamification for hybrid, both live and virtual, events. However, within this new standard, there is a large knowledge gap among event organizers of how to execute an esport experience and why esports dominance is necessary to incorporate into hospitality and tourism models. Through understanding esports’ majority consumer, Gen Z, and accurately reflecting esports culture, event organizers will assist the tourism economy through prosperous esport events.

This study synthesizes existing empirical results about the effect of personal innovativeness on the intention to use technology in hospitality and tourism studies published from January 2010 to March 2020 via meta-analysis. The meta-analysis with a random effects model was conducted on 29 effect sizes of this relationship documented in 28 studies collected from over 7,000 search results on Google Scholar and Scopus. The results of the analysis suggest a significant positive medium effect of personal innovativeness on the intention to use technology in hospitality and tourism research with the overall effect size (ESr) of .38 (95% CI = .32, .44, z = 10.62, p = .001). The study also found that the effect does not change significantly across industries (hotels, restaurants, and tourism and travel), types of technology by task (with transaction function and without transaction function), age groups (younger than 30 years old and 30 years old and older), and power distance cultural differences of the respondents (high-power distance and low-power distance cultures). Based on the results of this study, the authors suggest adding personal innovativeness as a construct in technology adoption models in future research in hospitality and tourism studies and continue investigating potential moderations that could explain variations in effect sizes of the impact of personal innovativeness on the technology adoption intention across different populations. From the industry perspective, hospitality and tourism organizations may rely on customers with high perceived innovativeness to serve as change agents and drive customer adoption of new technology.

With loyalty programs increasingly used as a competitive method by hotel brands, this study investigates the relationship between program size/satisfaction and brand direct website performance. Analyzing a unique database of loyalty program statistics, traffic levels/sources and engagement metrics from the top 50 global hotel brands, we find that size matters, with larger programs performing better in terms of both traffic and engagement, suggesting that efforts by hotel brands to grow membership are appropriate. Similarly, program satisfaction positively impacts both traffic levels and engagement, suggesting that brands should also focus on ensuring that existing members are happy with program benefits and operations. These findings are consistent irrespective of brand level, suggesting that all types of hotel brands can profit from leveraging loyalty programs.

This study explores how technology-mediated journaling can support memorable and meaningful tourism experiences (MMEs). The digital photo is the most common medium for travelers to keep a record of memorable and meaningful moments and share them via social media. We explore the potential of using these footprints for travelers to connect the implicit dimensions of their well-being. In particular, we draw reference from positive psychology, which emphasizes that human well-being is rooted in people’s implicit personal factors and psychological needs such as character strengths, motives, and values. Making the implicit explicit may help people to make a wiser choice that matches their own aspirations. To support people in (re)creating meaningful narratives, we created a proof-of-concept prototype by incorporating character strengths into the design of a digital journaling platform. This study involved ten participants and each of them created at least five MME narratives from their past journeys. In this article, we discuss the design concerns for such a platform and examine the effectiveness of the platform in producing meaningful narrative by collecting participant feedback, and looking into the character strengths that the participants draw upon in their MMEs. The result suggests that not only the platform supports the reminiscing of MMEs, but the narration also deepened their self-awareness and allowed the participants to connect their behaviors with their personality traits and implicit values. Some participants were able to identify meanings that were hitherto obscured to them. Implications for quantified travelers and smart tourism are discussed.

Interest in citizen science is growing, including from governments and research funders. This interest is often driven by a desire for positive environmental impact, and the expectation that citizen science can deliver it by engaging the public and simultaneously collecting environmental data. Yet, in practice, there is often a gap between expected and realised impact. To close this gap, we need to better understand pathways to impact and what it takes to realise them. We articulate six key pathways through which citizen science can create positive environmental change: (1) environmental management; (2) evidence for policy; (3) behaviour change; (4) social network championing; (5) political advocacy; and (6) community action. We explore the project attributes likely to create impact through each of these pathways and show that there is an interplay between these project attributes and the needs and motivations of target participant groups. Exploring this interplay, we create a framework that articulates four citizen science approaches that create environmental impact in different ways: place-based community action; interest group investigation; captive learning research; and mass participation census.

Citizen science is a promising field for educational practices and research. However, it is also highly heterogeneous, and learning happens in diverse ways, according to project tasks and participants’ activities. Therefore, we adopt a sociocultural view of learning, in which understanding learning requires a close analysis of the situation created both by the project tasks and the dynamics of engagement of the participants (volunteers, scientists, and others). To tackle the complexity of the field, this chapter maps learning in citizen science into six territories, according to where learning might take place: formal education (schools and universities); out-of-school education (science and nature clubs, summer camps, outdoor education, etc.); local and global communities (neighbourhood associations, activist associations, online communities, etc.); families; museums (science museums, art museums, zoos, and botanic gardens); and online citizen science. For each territory, we present key findings from the literature. The chapter also introduces our six personal journeys into the field of learning and citizen science, displaying their variety and the common lessons, challenges, and opportunities. Finally, we present four key tensions arising from citizen science projects in educational settings and look at training different stakeholders as a strategy to overcome some of these tensions.

In this chapter, we explore the landscape of citizen science across Europe, how networks have developed, and how the science of citizen science has evolved. In addition to carrying out a literature review, we analysed publicly available data from the European Commission’s Community Research and Development Information Service (Cordis). We also extracted information from a pilot survey on citizen science strategies throughout Europe, carried out within the framework of the COST Action CA15212. Our findings are complemented by case studies from COST member countries. Finally, we offer some insights, considerations, and recommendations on developing networks, utilising the COST Action and EU-Citizen.Science as capacity building platforms.

This book is the culmination of the COST Action CA15212 Citizen Science to Promote Creativity, Scientific Literacy, and Innovation throughout Europe. It represents the final stage of a shared journey taken over the last 4 years. During this relatively short period, our citizen science practices and perspectives have rapidly evolved. In this chapter we discuss what we have learnt about the recent past of citizen science and what we expect and hope for the future.

Evaluation is a core management instrument and part of many scientific projects. Evaluation can be approached from several different angles, with distinct objectives in mind. In any project, we can evaluate the project process and the scientific outcomes, but with citizen science this does not go far enough. We need to additionally evaluate the effects of projects on the participants themselves and on society at large. While citizen science itself is still in evolution, we should aim to capture and understand the multiple traces it leaves in its direct and broader environment. Considering that projects often have limited resources for evaluation, we need to bundle existing knowledge and experiences on how to best assess citizen science initiatives and continually learn from this assessment. What should we concentrate on when we evaluate citizen science projects and programmes? What are current practices and what are we lacking? Are we really targeting the most relevant aspects of citizen science with our current evaluation approaches?

Citizen science projects rely on public involvement, making a communication and dissemination strategy essential to their success and impact. This needs to include many aspects, such as identifying the audience, selecting the communication channel(s), and establishing the right language to use. Importantly, citizen science projects must expand beyond traditional top-down monologue interactions and embrace two-way dialogue approaches, especially when communicating with project participants. Further, to be effective, communication activities require good planning and dedicated resources. This chapter highlights the importance of communication and dissemination in citizen science; provides examples of successful strategies and identifies the factors that determine success; and describes some of the challenges that can arise and how to overcome these.

Adequate infrastructure for citizen science is constantly growing and has become increasingly important in providing support to citizen science activities, both nationally and internationally. Many types of citizen science infrastructures exist, with different functionalities. This chapter focuses on current citizen science platforms. The platforms addressed in this chapter are those which display citizen science data and information, provide good practical examples and toolkits, collect relevant scientific outcomes, and are accessible to different stakeholders, ranging from interested citizens to scientific institutions to authorities, politicians, and public media. We present current citizen science platforms in Europe and associated (inter)national citizen science networks and discuss how these platforms have become increasingly vital within citizen science. Based on these examples, we elaborate on challenges for citizen science platforms, such as establishing and financing platforms, designing user interfaces, maintaining platforms, promoting the usage of platforms, etc. We conclude with an outlook into potential development needs of citizen science platforms in the future.

In this chapter, we highlight the added value of mobile and web apps to the field of citizen science. We provide an overview of app types and their functionalities to facilitate appropriate app selection for citizen science projects. We identify different app types according to methodology, data specifics, and data collection format.The chapter outlines good practices for creating apps. Citizen science apps need to ensure high levels of performance and usability. Social features for citizen science projects with a focus on mobile apps are helpful for user motivation and immersion and, also, can improve data quality via community feedback. The design, look and feel, and project identity are essential features of citizen science apps.We provide recommendations aimed at establishing good practice in citizen science app development. We also highlight future developments in technology and, in particular, how artificial intelligence (AI) and machine learning (ML) can impact citizen science projects.

This chapter uses informed consent as a point of departure for the description of multiple ethical facets in citizen science. It sets out an overview of general ethical challenges in citizen science, from conceptual issues around social imbalances and power relations, to practical issues, such as how to deal with privacy for participants as well as data protection, intellectual property rights and other emergent issues. The chapter goes on to describe the different types of informed consent, particularly focusing on dynamic informed consent as the solution to the challenges described. Finally, practice-oriented recommendations about how to tackle some of the ethical issues raised in the chapter are set out.

In line with the growth in citizen science projects and participants, there are an increasing number of guidelines on different aspects of citizen science (e.g. specific concepts and methodologies; data management; and project implementation) pitched at different levels of experience and expertise. However, it is not always easy for practitioners to know which is the most suitable guideline for their needs. This chapter presents a general classification of guidelines, illustrating and analysing examples of each type. Drawing on the EU-Citizen.Science project, we outline criteria for categorising guidelines to enable users to find the right one and to ensure that guidelines reach their intended audience. We discuss challenges and weaknesses around the use and creation of guidelines and, as a practical conclusion, provide a set of recommendations to consider when creating guidelines.

In this chapter, over 30 surround microphone techniques are explained in detail and partly analyzed. Starting out with coincident techniques (XYXY-mic technique) with various patterns, via MS techniques to specialDolby Atmos systems such as AmbisonicsAmbisonics microphone (SoundField MicrophoneSoundField Microphone) and Bauer’s ‘Phasor ArrayPhasor Array (Bauer).’ We move on to spaced arrays for two-dimensional sound reproduction, starting from circular arrays, via OCTOptimum Cardioid Triangle (OCT) and ORTF SurroundORTF Surround, to the IRT CrossIRT-cross (mic array), Hamaski Square and ‘Microphone Curtain’ designs. A large number of ‘Tree’-based techniques is examined, which all have their roots in the famousDECCA (record company) ‘DECCA-treeDecca-tree’ arrangement: AB-PCAB-Polycardioid Centerfill (AB-PC) Surround, CHAB 5.0CHAB 5.0, Fukada treeFukada-tree, Polyhymnia PentagonPolyhymnia Pentagon, Streicher’s ‘Surround SoundDECCA (record company) DECCA-treeDecca-tree’ and XYXY-mic technique triXY-tri, to mention just a few. To finish up, there is a section on ‘BaffledBaffled mic techniques and 3D Techniques,’ starting out with the KFM360 sphere microphone, various baffled surround-mic systems, the HolophoneHolophone microphones, DPADPA microphones ‘D:mension 5100,’ Sony sphere-arrangement, the ‘EigenmikeEigenmike®®,’ Jecklin’s OSISOptimal Sound Image Space (OSIS)-System, the Pan-AmbiophonicPan-Ambiophonic (2D/3D) 2D/3D system and theBACCH™ (3D audio) BACCH(™) 3D Sound system. A short look is given to ‘Immersive AudioImmersive audio’ systems like ‘Auro 3DAuro 3D,’ ‘Dolby AtmosDolby Atmos’ as well as related microphone techniques.

A Blockchain is an immutable, tamper-proof, shared ledger of state changes of a digital asset. It is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value. This digital ledger is managed via a distributed network across many nodes that can verify and confirm those transactions through consensus. The implications of the technology are far-reaching but there are conditions that should be met in order for Blockchain to be a viable solution. The purposes of this research are to (1) explore the current Blockchain use cases in Shared Services (2) understand the value created by Blockchain in Supply Chain Management and (3) study the tactical challenges in adopting a Blockchain strategy in Shared Services. In addition to a literature review conducted, we conducted in-depth interviews with selected Shared Services Leaders and experts. Results of our research indicate that Blockchain technology can deliver on expectations and implementation in Shared Services organizations will require simple steps. This study provides the data necessary for executives to build a business case for applying Blockchain technology in Shared Services and investigates the potential that Blockchain has to revolutionize industry and deliver gains in speed, security, transparency, traceability and accountability for a wide range of business processes.

The digital transformation brought new opportunities as well as challenges to the business services sector. New digital technologies like cognitive automation, blockchain, or process mining could facilitate all significant business aims service centres. These could contribute not only to the efficiency metrics of operation but to the effectiveness of the business as well. The different levels of digital transformation presented in this paper all contribute to these benefits, and the future holds new opportunities with the further advancement of cognitive solutions. These technologies have already proven their capabilities, but their implementation is always difficult and should be custom-made. Quantitative and qualitative research was conducted to discover business practices related to the digitalisation of the business services sector in a Central and Eastern European country. This paper provides insight into a major Hungarian-based business services centre with three unique cases of digital technology implementation projects. Through these cases, the paper reveals the process of selection and introduction as well as outcomes of digitalisation projects in the examined company. The paper ensures an overview of new technologies that could be used in the sector to build a framework called Business Services 4.0.

We examine jobs on a popular freelancing platform that are marked or described as potentially ongoing jobs. We consider them to have characteristics of outsourcing tasks, but they are geared towards individuals rather than companies. Our empirical research shows that such jobs are offered in programming like in traditional IT outsourcing but also in many Internet-related jobs like content writing and writing in social media, search engine advertising, or e-mail marketing. Most employers are located in the U.S. or other English-speaking countries. This makes English language skills very valuable. The data indicate that jobs are often outsourced to countries with lower wage levels. However, employers often try to outsource them to the country where they are located, or at least to a country in a similar time-zone. In such cases, they are obviously willing to pay more for the work in order to have better communication possibilities. Outsourcing to individuals creates opportunities for these individuals. However, given their relatively weak position towards outsourcing companies they risk more and probably earn less than employees in these companies or at outsourcing suppliers.

The purpose of this paper is threefold: firstly, it provides a stocktake of the current (parlous) state of the decaying, and so-called, liberal world order. Secondly, it identifies the key obstacles inhibiting the prospects for the reform of that order. Both decay and the obstacles to reform are exacerbated by the COVID-19 pandemic. Especially, it looks at the equally parlous relationship between the USA and China, as it has unwound in recent years and asks how the future development of the US-China relationship will determine the reform of world order over the next five to ten years; again, a question profoundly influenced by COVID-19. Thirdly, the paper asks what role the EU 27 might play in the debate over, and practice of, the reform of world order after Brexit.

“Civilian Government Agencies” describes the array of U.S. government agencies encountered on the ground in peace and relief operations including the traditional foreign affairs departments—State, USAID, Defense, Commerce, and Agriculture—but also Treasury, Justice, Homeland Security, and Health and Human Services. Although this chapter deals mostly with U.S. agencies, it also includes sections on agencies in the United Kingdom, Sweden, Japan, and Canada. We have focused on efforts to improve the capacities of civilian agencies in complex operations. We have also included material on the legal authorities and appropriations constraints that agencies operate under, coordination across agencies, and monitoring and evaluation, as well as a section on humanitarian response under USAID’s general direction.

This chapter describes non-governmental organizations that respond to humanitarian emergencies, natural disasters, and violent conflicts and provide peacebuilding, long-term development, and advocacy. It provides basic information regarding the structure, staff and missions of NGOs found in peace, stabilization, and relief operations. It also includes a discussion of the growth of civil society as an important component of peacebuilding as well as the challenges of on-the-ground coordination among the NGO community and between NGOs and other civilian and military actors. This chapter also discusses the difference between neutrality and impartiality in terms of humanitarian assistance, as well as the pros and cons of NGO activity and the issues being debated within the NGO world itself.

The introduction describes the purpose of the book and looks at the on-again off-again nature of the international community’s response to conflict and crises over the years, the evolving nature of conflict, and the continuing need for international actors to understand and learn how to work most effectively with other actors operating in the same space.

The paper deals with evaluation of the quality of public service infrastructure in the city of Kronstadt, the historical part of Saint-Petersburg agglomeration. Public services are considered as FMCG, cultural and recreational venues people use in everyday life. We consider the quality of public services through a set of objective (availability, accessibility, variability) and subjective (users perception) indicators. We measure the quality of public service infrastructure based on the data from open digital sources, such as Technical Passports of Houses from Open Data of Saint-Petersburg Platform, Google Maps, Google Places, and validate usability of services based on a sociological survey. We illustrate our analysis with maps which provide a detailed view on the localization, accessibility, variability of the service infrastructure. We conclude that public service infrastructure in Kronstadt does not address the needs of the dormitory areas which make up one third of all citizens of the city.

The Internet forms not only new cyberspace but also has a significant impact on the perception of time and its organization. Focusing on the phenomenon of temporal behavior in social media, the current study aims to identify factors that can determine the dynamics of communication in the comments of the popular Russian social network Vkontakte. The research is based on data from six major online media: “Meduza,” “Lenta.ru,” “Rossiyskaya Gazeta,” “Novaya Gazeta,” “Mayak,” and “Russia Today.” We examine the frequency of publications, the dynamics of communication, the temporal distribution of comments, and the post response rate. The identified four temporal behavior models described as “Discussion media,” “Stimulus is a response,” “From call to call,” “Timeless or Silence is gold,” provoke assumptions about the possible causes of differences in the dynamics of communication between Russian Internet users.

Research has been proposed to determine an approach for studying cyber-social trust in different social spheres. A survey to better understand the trust Saint Petersburg citizens’ have in information technologies was conducted using a Social Construction of Technology (SCOT) approach. From the 600 respondents to this survey, the sampling error does not exceed 4% with a 95% level of reliability. The research demonstrates a new approach to a cybersocial trust construction. The questionnaire contained variables to evaluate the experience of use and the level of trust in new technologies in the areas of interaction with the government, the economy, healthcare, education, and interpersonal communication. According to the survey data, the category of cyber social trust was defined as the synergy of three components: institutional, transactional, and informational trust. According to the study, the experience of respondents strongly determines their willingness to use technology in various fields.

Online protest activity has become a trend of the last few years, attracting the attention of both theorists and practitioners of protest movements and social and political campaigns. The events of the last few years allow us to say that social media play a significant role in protest activity around the world. In 2019, one of the most visible and appealing forms of protest activity was environmental activism, which, however, increasingly had politicized features. In this paper, the authors define online protest as well as the role of social media in this process. The perspectives on environmental protest discussed in this paper are used to analyze three cases. Based on them, the main topics and directions that are used by environmental protest initiators to mobilize social media users are identified. Each of the selected topics of protest actions is analyzed in terms of the impact on the protest in general, as well as on users’ activity and their desire to support a certain direction of protest.

This paper covers the results of a comparative analysis of the effectiveness of passive and active data collection methods for the purpose of extracting mentions of adverse drug reactions (ADRs) in Russian. In terms of their effectiveness, two systems of data collection were compared: a data mining system for gathering post and comment text content from social media, and an experimental chatbot conversational survey, integrated into a thematic community and targeted at collecting ADR reports. The study was conducted on VK, a Russian social network, on a community dedicated to the discussion of user experiences with taking drugs for treating mental illnesses. A comparative analysis of the comprehensiveness of data obtained by the passive method and the chatbot was carried out. The results show that an active information collection system allows subsequent information processing to be performed more effectively. Based on the results, areas for further development of conversational surveys for medical research were identified.

The article is devoted to the analysis of civic activity in modern Russia. The article presents the results of a longitudinal study of civic activity in Russia since 2014. The study is conducted by a survey of experts. Particular attention is paid to the analysis of the development of online and offline civic activity.Considerable attention is paid to the analysis of mobilization and demobilization in civic activity. It examines what forms of organizations are most significant in civic engagement, as well as how authorities react to their activities, what tools are used to demobilize citizens.The research show that the degree of development of civic activity has remained at approximately the same level for several years. At the same time, on-line activism is more developed than off-line. It seems that online activism is more massive and affordable, less labor-intensive for ordinary participants. At the same time, the Internet provides a fairly diverse set of tools, the application technologies of which are developing. Internet technologies are used as a mechanism by which political action can be seen by authorities and the public. At the same time, the state is forced to respond to such changes and is stepping up to regulate various forms of activity on the Internet.

In this paper we present a corpus of Russian strategic planning documents, RuREBus. This project is grounded both from language technology and e-government perspectives. Not only new language sources and tools are being developed, but also their applications to e-government research.We demonstrate the pipeline for creating a text corpus from scratch. First, the annotation schema is designed. Next texts are marked up using human-in-the-loop strategy, so that preliminary annotations are derived from a machine learning model and are manually corrected.The amount of annotated texts is large enough to showcase what insights can be gained from RuREBus.

The prevalence of technology and use thereof by part-time learners during lectures presents particular challenges to facilitators of learning. Devices used for learning can be misused for off-task activities, lowering engagement levels, and negatively impacting learning. This research investigated how learners use technology to contribute to learning, but also disengage from the learning process, and contrast it with their personal engagement to determine the potential impact. The quantitative data provides evidence of a relationship between on-task use of technology in the classroom and higher engagement levels in the learning process. Analysis reveals three insights about learning in the age of digital transformation. Firstly, the design of learning interventions should be as interactive as possible to ensure that learners do not disengage. Secondly, facilitators of learning need to ensure their learning design incorporates activities making use of the technology and thus create an environment of digital engagement and active learning. Finally, faculty that use technology to individualize learning should enable students that are working full time to become creators of media and not just consumers.

Today art museum is facing the challenge of adapting it’s mechanisms of keeping and presenting the works of art to spectators belonging to the communication society. Therefore, a museum gets more and more engaged in the process of digitalization using such newer technologies as internet of things, virtual reality, artificial intelligence, bid data design etc. The aims of a museum are currently shifting from traditional keeping the art pieces and studying them to—developing a scientific networks, announcing the highlights in social media and creating platforms which present digitalized pieces online allowing a viewer to collect the information through the web, moreover, an offline visit could be guided by a specified application customized to fit the necessitates of each user. An art institution today is supposed to be flexible and democratic enough to create an engaging, immersive area for a visitor to interact with, in other words, we argue that a museum armed with newer technologies is supposed not only a to secure and present the works of art but also to incorporate these pieces into the bigger flux of information, make them visible and important to viewers, to create the conditions for a lasting dialogue. We argue that this process involves not only the technical development of a museum, but also a new approach no narration of art history.

Data-based and data-driven decisions are at the core of digital government transformation. However, the more the data is to be used to guide policy development, the higher are the requirements to the data accuracy and readiness. Larger reliance on data to inform policy decisions should not lead to increased reporting requirements and hence excessive administrative burden on businesses. Therefore, identifying and reducing duplication in statistical data should be performed at the early stages of the government digital transformation. Given the constantly increasing number of strategic documents and continuous amendments to the list of statistic indicators measured, there is a need for an instrument allowing for timely identification and elimination of possible duplication in statistical and other indicators.In this paper we propose a methodic approach to identifying and evaluating possible duplication in statistical and other administrative indicators which is based on a partially automatable algorithm complemented by expert evaluation. The results of piloting this approach on a set of about 6,000 statistical indicators suggest that it could become a useful tool for data management that would allow to improve the quality of aggregated data, on the one hand, and reduce administrative reporting burden on businesses – on the other. The proposed approach could also be applied in a broader context, i.e., for the analysis of strategic planning documents, and may be of interest to practitioners from other countries where the quality of statistical data and duplication of administrative information is considered a barrier for further government digitalization.

The study identifies the need to develop the entrepreneurial competencies of specialists in business and management in the digital economy age and reveals the understanding of opportunities and risks of the digital transformation of the economy. It provides a theoretical framework, based on a scientometric analysis of publications on digital economy with VOSviewer Software and an extensive literature review, emphasizing the necessity of entrepreneurial competencies in the digital economy. The results of the exploratory qualitative study show how undergraduate students in management and business explain what digital economy is and who is the manager in the digital age, and explain opportunities and threats that they associate with the digital transformation. The paper discusses the results and major problems concerning the students’ perception of the digital economy and a manager in the digital context. This study contributes to the research that focuses on the development of management and entrepreneurship in the digital economy.

Automatic evaluation of public opinion is an actual problem in many areas, including both governmental and private sectors. There is number of scientific schools and corporations which work on to solve the problem of automatic evaluation of publications in media, social networks and other internet resources, in order to solve such problems as evaluating public image of a company, product or persona, evaluating work of PR departments and agencies, analyzing the most socially significant and resonant newsmakers and issues. The problems involve area of natural language processing and understanding, which is considered to be technologically and mathematically complex, and is nowadays being solved using deep learning models, which require a large marked dataset with texts of similar domain, which is hard and expensive to obtain. Another problem of such systems is performance issues. In this work an informational system is described, which attempts to solve the outlined problems. In the paper an approach is proposed, which allows to classify the most important/positive/negative/resonant topics and publications, and to analyze their dynamic characteristics. The proposed approach is not based on manual creation of keyword dictionary, or labelling of big amounts of documents and allows to evaluate documents according to arbitrary criterion. The approach was verified on one criterion by comparing it’s results to a dictionary-based system.

The research project we are conducting is devoted to text emotional analysis. In this paper, we report the preliminary results of the non-discrete data assessment method, which uses an original interface developed to annotate texts according to emotion model known as Lövheim Cube. Swedish neurophysiologist H. Lövheim put eight basic emotions in the cube vertices according to the particular combination of three monoamines triggers each of them. We took four supporting diagonals of the cube and mapped them onto assessment scales: Distress/Enjoyment, Rage/Disgust, Shame/Excitement, Fear/Surprise. 172 human assessors were asked to adjust the pointer of a slider between two opposite emotions on the scales after having been read each of 48 text fragments retrieved from Russian social network VKontakte. By converting labeled scalars into spatial coordinates in the cube space, we obtained a set of comparable evaluations. The effectiveness of the approach has been validated using the Intra-class correlation metric. The proposed method offers noticeable benefits when compared to the discrete assessment procedure, giving to each text a multidimensional evaluation, which is closer to the natural text perception while reading.

With cloud robotics, particularly robotic vision available wi-thin a household, human are able to live a convenient and safer life in an ambient assisted living environment. Recent advances in computational intelligence including neural network improves the computational capability of the robotic vision to better understand the environment. Recently, internet hoaxes that affected the social community greatly have raised strong awareness among public in parental control and the content that the youngster can view. Therefore, this paper focuses on filtering movies or videos that is not suitable for youngster by attempting to identify movie genre. Movie genre classification has been investigated in recent years, but there exist noise in normal videos referred as generic frames, as mentioned in [1], that makes differentiation movies with similar frame difficult. A filtering approach is proposed in this paper in order to identify generic frames within the video and discard them from genre classification process, in order to improve genre classification performance. Experiment shows that the filtering approach are able to improve action genre class, but have difficulties and improving other genre classes.

Digitalität ist eine Zumutung. Damit ist kein Widerspruch zu den Vorteilen digitaler Technologie aufgemacht. Kein Gegensatz zur Erleichterung, Hilfe und ganz eigenen Produktivität durch Computer und deren Vernetzung, wovon Menschen in zunehmenden Bereichen des Lebens profitieren.

Was Interfaces sind, zeigt sich daran, was sie leisten. Interfaces stiften Verbindungen. Sie bilden und erlauben Übergänge und Vermittlungen. Unweigerlich stehen sie dabei auch für die Trennung jener Bereiche, zwischen denen sie Übergange einräumen.

Mindfulness has become quite popular. Both in scientific research and within regular media, the attention for the beneficial effects of mindfulness has increased. In the business world, claims on the effectiveness of mindfulness for well-being, focus, and performance are thrown around rather carelessly. In recent years, organizations are also providing more mindfulness courses for their employees. In the academic world, research on mindfulness in general, as well as on the effect of mindfulness in organizations, is on the rise. As a reaction to the increased “hype,” some scientists are concerned about overstatements on the effectiveness of “McMindfulness,” and the lack of ethical framework surrounding the application of mindfulness in both treatment settings and organizations. Therefore, it is important to remain critical and to develop a nuanced view on the effectiveness and use of mindfulness for both leaders and their employees in organizations. In this review chapter, we provide an overview on the research on leader mindfulness and the possible working mechanisms, after which we formulate some critical remarks and give practical evidence-based advice on the application of mindfulness in organizations. Although mindfulness seems to have beneficial effects on leader and employee well-being, our goal is to provide a nuanced view of the up-to-date research on leader mindfulness, to support future research, theory building, and practical applications in the work place.

The topic of well-being and flourishing is a dual-sided story that often communicates benefits enjoyed by one group without sharing the associated costs levied on others. Such costs are rarely revealed by those who have no voice, opportunity, or desire to communicate details describing their experiences on the other side of the well-being equation. As such, this work invites a conversation around well-being and human flourishing that communicates a personal, inner language using stories of people viewed as objects within the mainstream society. Object theory has been used to explain how physical objects can inform us of a past reality, whether the existence of a societal condition or an historical event. In a broader description, object relations theory has been applied extensively in psychoanalytic psychology to explain both the process of developing a psyche in relation to others and, by adding psychodynamic and shadow self theories, better understand how people relate to others and situations in their lives as shaped by perceptions and past experiences. In this study, we use stories, the extant literature, and real-life experiences captured using Photovoice as a research approach to personify object theory and apply it to people today who represent objects in institutions and societies. The topic is of interest in management as an adverse organizational condition that can erode authenticity and create structural bias in business settings which can inadvertently extend to business practices and decisions. We use this concept to explain a central shortcoming in management that hinders the productivity of organizations when leaders subjugate people as objects for the good of the organization. We offer an alternative view of the spiritual relationships that can exist between people in community that serves to develop healthy business environments and improve organizational outcomes.

Well-being is a multifaceted concept in the context of welfare for human enterprise. The Eastern spiritual traditions take a holistic approach to well-being that places human beings in an ecological/natural context. Maharishi Patanjali’s Yoga Sutras are an ancient scripture that provides a comprehensive, multilevel toolkit of principles and practices leading up to union with pure consciousness, or kaivalya. This chapter will describe the eight limbs of Yoga Sutras that provide well-being at the level of the individual as well as the society. It will then describe some famous case studies of yogis creating collective well-being using parts of the Yoga Sutras in unique entrepreneurial ways to achieve success for whole societies. Mahatma Gandhi raised the moral well-being of the Indian population through the practice of yamas and niyamas. Swami Ramdev is helping improve mental and physical well-being of millions of people using asanas and pranayama. Maharishi Mahesh Yogi helped relieve the stress and anxieties of millions of people, especially in the Western world, and gave them a taste of blissful living through the practices of dhyana and samadhi. We will explore how existing and new tools based on the Yoga Sutras can help unite humanity and address the complex challenges in the service of universal flourishing.

The concept of wellbeing is certainly not new. Both employers and employees continue to find ways and strategies for improving and sustaining wellbeing at the individual and organizational levels. The chapter attempts to address the issues and challenges in developing institutional strategies. Employees are motivated to enhance and sustain improved levels of wellbeing to be able to contribute to work as well as their satisfaction with life in general. The personal level emphasis for the employee is important and also a focus of the chapter. In order to address institutional and personal level approaches to wellbeing, a primary goal of the chapter is to review recent literature on wellbeing, identify key constructs or dimensions that constitute wellbeing, develop a conceptual model, and present implications for practice. The review of literature on wellbeing offers a way to conceptualize a model and a typology for understanding the different dimensions that constitute wellbeing as well as present an emergent model. The new model offers implications for managers as they harness the full potential and value of their employees by developing and deploying practical strategies for workplace wellbeing.

Hiring and advancing individuals based upon talent, credentials, proven performance, and level of determination is often obscured by exclusionary employment practices and discriminatory – whether latent and patent – mindsets. While ethical workplace decisions are generally predicated upon a fundamental understanding of fairness and a commitment to making the right decisions for all workers, oftentimes employers fail to exercise uniform and equitable judgment until there is mandatory direction. Thus, ethics in the workplace often starts with the law, its comprehensive understanding, and the unwavering compliance with all relevant legislative enactments. In recent years, judicial interpretation of anti-gender discrimination laws in the USA has embraced a more liberal definition and application, arguably fostering a more inclusive atmosphere in the workplace.

Work is fundamental to human flourishing. A toxic work environment can lead to work alienation and disengagement, adverse to human flourishing. Toxic leadership, including sexual harassment by managers, a form of bullying, creates a toxic work environment. Workers value transparency and fairness. The typical way that sexual harassment complaints are resolved in work organizations involves mandatory arbitration and nondisclosure agreements. Not only are these processes non-transparent, but they also enable the continuation of the toxic behavior. The #MeToo movement led to whistleblowing about sexual harassment at the Weinstein Company, Fox News, CBS, NBC, and Uber. Investigations conducted at Uber, following a complaint by a female engineer posted on a public blog, resulted in the resignation of the founder of Uber as CEO and widespread change in corporate procedures, including performance management and compensation systems. New York, New Jersey, and California all have prohibited secret nondisclosure agreements settling sexual harassment complaints. High-tech companies including Uber, Microsoft, Facebook, and Google have voluntarily abandoned mandatory arbitration of sexual harassment claims. Significant culture change is required to eradicate sexual harassment in the workplace, so that the sex roles of female workers are not defined as salient, but rather female workers are judged in terms of the effectiveness of their job performance. Performance management and compensation systems for executives are required to create real culture change in work organizations. The focus on improving organizational transparency and fairness would appropriately be expanded including race harassment and gender identity issues in the workplace.

This chapter aims to substantiate a theory-driven and context-specific conceptualization of employee well-being for Chinese employees. Drawing on three primary defining characteristics of well-being in psychology, i.e., the distinction between hedonia and eudaimonia, the imperative consideration of social dimension, and the indispensable attention to negative affect, this chapter conceptualizes Chinese employee well-being as a multidimensional concept consists of positive affect, individual well-being, social well-being, and negative affect. The qualitative and quantitative data from 544 Chinese employees support the proposition of multidimensionality but cannot distinguish individual well-being from social well-being. Aligning with this context-specific profile of employee well-being, future research would better clarify employee well-being-related concepts and select appropriate measures to address specific research gaps. The results also generate context-specific recommendations for management practitioners to improve employee well-being in China.

Since the beginning of human time, work has been part of life, sometimes dreaded and sometimes enjoyed. Shifts in technology and societal trends have brought about new insights into what it means to live and work. Once relied upon for strength and muscle, humans are now more than ever becoming knowledge workers needed for the power within their minds. No longer can organizations ignore the well-being of workers if they want to succeed in a globally competitive environment. To be leverage the power of the workforce of the future requires a new approach to designing organization. Our design imagines a future where both workers and organizations can flourish live never before.

Workplace Wellness programs offer employees healthy benefits without the need to sacrifice family time. Employers seek lower healthcare costs and improved productivity from healthy employee habits. Most Wellness programs seem to focus on physical health and screenings while not considering the challenges employees face through workplace stress and even project failure. The author provides support for a comprehensive Workplace Wellness program grounded in Redemption. Such a program considers the challenge of talent acquisition; the manager’s moral responsibility for employee development; how limiting employee Wellness programs can cause them to be ineffective; and the need for Wellness programs to be more than attempts at social redemption through physical fitness. A blueprint for Workplace Wellness programs grounded in Redemption is offered at the end of the chapter.

Haben Sie die Entscheidung erstmal gefällt, einen Wissensblog zu starten, und haben Sie ein Herzensthema gefunden, so ist die Versuchung groß, einfach loszulegen. Auf Online-Plattformen wie Wordpress.com dauert es gerade einmal fünf Minuten, um einen neuen Blog einzurichten. Die Kosten dafür liegen bei Null.

Die Corona-Krise hat gezeigt, wie viel Aufklärungsarbeit Wissenschaft in der Gesellschaft zu leisten hat. Beweise und harte Fakten reichen für nicht aus, um Verschwörungstheoretiker, Wissenschaftsskeptiker und andere Zweifler umzudrehen. Dafür bieten sich in aller Regel Storytelling-Techniken an.

Ist Ihr erster Text erst einmal verschickt, passiert in der Regel: nichts. Wenn Sie einen neuen Blog ins Netz stellen, weiß die Welt nichts davon. Und die Konkurrenz ist enorm. Sie müssen also wie jeder gute Unternehmer denken und auch Werbung einplanen, Artikel auffindbar sind.

Wo wollen Sie Ihre Blogs veröffentlichen? Diese Entscheidung steht noch aus. Sie haben dafür eine Reihe von Optionen. Option eins ist das Veröffentlichen auf Ihrer eigenen Webseite, als Einzelblog.

The Global Data on Events, Location, and Tone (GDELT) is a real time large scale database of global human society for open research which monitors worlds broadcast, print, and web news, creating a free open platform for computing on the entire world’s media. In this work, we first describe a data crawler, which collects metadata of the GDELT database in real-time and stores them in a big data management system based on Elasticsearch, a popular and efficient search engine relying on the Lucene library. Then, by exploiting and engineering the detailed information of each news encoded in GDELT, we build indicators capturing investor’s emotions which are useful to analyse the sovereign bond market in Italy. By using regression analysis and by exploiting the power of Gradient Boosting models from machine learning, we find that the features extracted from GDELT improve the forecast of country government yield spread, relative that of a baseline regression where only conventional regressors are included. The improvement in the fitting is particularly relevant during the period government crisis in May-December 2018.

Press releases represent a valuable resource for financial trading and have long been exploited by researchers for the development of automatic stock price predictors. We hereby propose an NLP-based approach to generate industry-specific lexicons from news documents, with the goal of dynamically capturing, on a daily basis, the correlation between words used in these documents and stock price fluctuations. Furthermore, we design a binary classification algorithm that leverages on our lexicons to predict the magnitude of future price changes, for individual companies. Then, we validate our approach through an experimental study conducted on three different industries of the Standard & Poor’s 500 index, by processing press news published by globally renowned sources, and collected within the Dow Jones DNA dataset. Classification results let us quantify the mutual dependence between words and prices, and help us estimate the predictive power of our lexicons.

Financial processes are frequently explained by econometric models, however, data-driven approaches may outperform the analytical models with adequate amount and quality data and algorithms. In the case of today’s state-of-the-art deep learning methods the more data leads to better models. However, even if the model is trained on massively parallel hardware, the preprocessing of a large amount of data is usually still done in a traditional way (e.g. few hundreds of threads on Central Processing Unit, CPU).In this paper, we propose a GPU accelerated pipeline, which assesses the burden of time taken with data preparation for machine learning in financial applications. With the reduced time, it enables its user to experiment with multiple parameter setups in much less time. The pipeline processes and models a specific type of financial data – limit order books – on massively parallel hardware. The pipeline handles data collection, order book preprocessing, data normalisation, and batching into training samples, which can be used for training deep neural networks and inference. Time comparisons of baseline and optimized approaches are part of this paper.

The extensive Brazilian territory endows its Navy with more than 350 facilities with several distinct activities that transcend military operations. Understanding the variation of all the essential and common costs of those facilities proved to be a challenging and relevant task. This paper presents a machine learning approach to support the decision-making process based on data that represents several facilities attributes, where models were trained, and those with the best performance were further analyzed. Besides data limitations, our results show that predictions and explanations derived from the models can be applied to support decision-making within the organization and contribute with insights to improve management over its resources.