HCI International 2020 – Late Breaking Papers: Interaction, Knowledge and Social Media

Software crowdsourcing platforms allow for wide task accessibility and self-selection, which require participants to interact with a wide range of task options. This increased accessibility enables crowd workers to freely choose tasks based on their skills, experience and interests. However, the inconsistencies in crowd workers’ comprehension and interpretation of the designs of different tasks and the platform interaction strategies may introduce task uncertainty into the selection process. This may result in low performance, which can diminish the quality of the crowdsourcing platform. Previous studies show that the quality of the outcome of these systems depends on different design parameters in both social and technical contexts. Therefore, through the lens of Socio-Technical Systems, our experimental study quantifies and compares 30 participants’ behavior and performance throughout their interaction and selection of different software tasks via an online-based tool named “SoftCrowd,” using different design strategies and task features. Results showed a significant relationship between task submission rate and platform design, including interaction strategies, task ambiguity and task instruction design. These findings suggest that our proposed design factors may have unanticipated effects on the quality of crowdsourcing, calling for more studies of crowdsourcing design to inform better strategies for various aspects of platform design.

The paper deals with forming the descriptive similarity based on algorithm and a computer program for the decision making support in order to select the suitable solution for implementation from portfolio of the existing experiences related to public transport from various cities, especially in Smart Cities. It helps to satisfy needs in six fields of Smart City and to form rapid decisions for the problems solving. The deeper focus of the work is to develop tools for supporting a decision-making process in which computer systems and people inevitability to participate together. People will not be able to process and analyze the required amounts of data within the required time. However, computers cannot, in principle, decide for humans what to consider as equivalent, what is appropriate and inappropriate for humans. This work focuses on those aspects, which are related to the numerical evaluation of similarity that are needed to make decisions based on analogy, higher prevision of descriptions.

Since the year of 2011 when urbanization of China reached 50%, “Urban Renewal” has become the hot topic among scholars from all industries of the society. Meanwhile, there appeared relevant discussion and researches against the methods of urban renewal. Compared with the previous developing mode which takes city expansion as the main stream, the comprehensive programme in large scale is preferred. At present, on facing the urban renewal situation switching from increment to stock. Small scale, local and progressive renewal method is gradually becoming the main stream. The community unit was one of the important parts of city structure, it is unique and could not be replaced on historical value and social meaning. In this way, when considering to melt it into current urban development, multi intervening is more required. It’s not only about the physical fusion in view of traditional meaning, but also includes the fusion of social environment. This thesis takes Xinhua Community of Shaoyang City as the case, regards the optimization and adjustment of all plots, as well as the coordination of benefit of all aspects as the entry point, with the grand background of “wiping off unitization”, to reconsider the relation between community units and all hierarchies of the city, as well as the way how community units blend into city.

We present the design research process towards a novel learning technology to improve instructional documentation in makerspaces. Our focus is on the ways in which smart tools can better support learning practices, with a particular emphasis on role of documentation plays. We first describe a co-design process with educational stakeholder that generated concepts for NFC-enabled forms of hybrid documentation. This solution developed offers a process for coupling physical tools, parts and materials to online resources in order to help make documentation ready-at-hand for learners. Findings from a subsequent focus group led to a refined implementation. Our preliminary evaluation in a high school settings highlighted the value of integrating online documentation formats to support youth navigating a broad array of fabrication tools and parts. Educators valued the solutions ability to support self-directed learning and to increase student access and agency with instructional resources.

The purpose of this paper is to explore the perceptions of healthcare professionals (HCPs) in the countries of India and Pakistan, that impede knowledge management practices by adopting mobile technologies in healthcare. An exploratory study was conducted among healthcare professionals in India and Pakistan to assess their perceptions regarding knowledge management practices using mobile applications in their working environment. This cross-sectional qualitative study used semi-structured interviews with healthcare professionals in both India and Pakistan. The interviews were analyzed using a thematic analysis, which revealed three major themes. These themes being: Medical education and training, Collaboration between HCPs, and Patient health education. Findings indicate that the HCPs associated with mobile technologies in healthcare in India and Pakistan generally view it in a functional manner, rather than in an explicit manner. The mobile healthcare technologies in use are looked upon as an alternative solution for clinical purposes such as viewing diagnostic reports or providing initial information to the patients, and many more. The recognition of the idea of explicit and tacit knowledge is not usual among the HCPs. Therefore, the knowledge-sharing ability of mobile healthcare technologies is understood below par and often underutilized.

The left-behind children in China are children who remain in rural regions of China while their parents leave to work in urban areas. The lack of infrastructure and parental support have led to a host of additional challenges for left-behind children like quality education, physical well-being, and healthy social relationships. As a previous study, we analyze the psychological needs of specific age groups based on the educational methodology of school-age children. Children who are overpraised, on the other hand, might develop a sense of arrogance. Clearly, balance plays a major role at this point in development. The idea is that human psychology grows through interaction with the surrounding people. The psychological problems of special children called “The left-behind children” are extracted. We propose communication tools to address these issues. This method will be used to solve psychological problems that “The left-behind children” have. We make prototypes from ideas and conduct experiments and evaluations. You can repeat such a review process many times and use effective communication tools. He thinks that “absent children” can solve psychological problems caused by growing parents because they do not have time to attend.

Renders or digital images of high quality and visual effect based on a 3D model or scenes made in a specialized computer program are generated along the chain of realization of animation products. A render is generated from a series of calculations between formulas and algorithms on the model that simulate the bounces of light rays on 3D objects in the scene and software that performs a Raytracing or tracking of the surfaces generated through a virtual camera that is integrated into the process.A 3D superior or production animation product would imply extensive rendering times, which is expressed in project costs per machine use. The carbon footprint of CO2 emissions imply on animation projects has been poorly or non explored, so this document presents an empirical experience that puts on the table a free and efficient alternative to optimize rendering processes in digital animation projects based on local machine adjustment and measurement techniques aimed at reducing carbon footprint, process flow and labor costs.

Nowadays, there are many opportunities to see maps on smartphones and tablet devices. The maps we use every day have no information about the slope, and we don’t know if a road is uphill or downhill. In particular, in hazard maps that map the predicted damage caused by natural disasters and the extent of the damage, slope information is important for understanding which route to follow during evacuation. Therefore, we thought that it is possible to grasp the inclination information when tracing the road by feeding back the force sense to the touch panel operation. In order to present the force sense on tablet devices, we employed SPIDAR-tablet. In our previous research, this device had a weak force sensation. Therefore, in this study, we strengthened the force by replacing the motor and rebuilding the frame. In addition, we have developed a new map application that can output the slope information of the traced road as an easy-to-understand force sense. Then, using this application, we conducted an evaluation experiment of the effectiveness of presenting the inclination angle of the road by force. As a result of this experiment, it was found that the difference in the inclination angle of the road could be detected by force. As a future perspective, we would like to present more disaster information to the hazard map by adding not only force information but also sound and temperature.

In this paper we present Jarvis, a multimodal explorer and navigation system for biocuration data, from both curated sources and text-derived datasets. This system harnesses voice and haptic control for a bioinformatic research context, specifically manipulation of data visualizations such as heatmaps and word clouds showing related terms in the dataset. We combine external speech systems with Clustergrammer [1] for the generation of bioinformatic queries, the BoB interface [2] for answering queries in that domain, and the VoxML framework [12] for manipulating the results and semantic grounding. We deploy the resulting system to iOS on an iPad for use by researchers over a test dataset of gene expression in tumor samples. The intent is to integrate multimodal control (here voice and haptics), so as to facilitate interaction with and analysis of data, taking advantages of using both modalities.

The original intention of this research is to spread Chinese culture. When communicating with foreigners, I discover quite a lot of them hold a view that Chinese culture is not easy to get to know and further be taken into use of daily life. Then I believe the first step I need to do is to let foreigners feel the easy-going aspect of Chinese culture. In this research, we choose the direct points of people in different areas of China as our starting point to make introduction of Chinese culture rather than make utilization of traditional geographical, historical and cultural classification pattern. Thus, current and real Chinese culture can be directly opened out in front of those foreigners who have desire to get to know China through self-experience, daily life and emotional memories. I reckon it would be far better to introduce China by daily details description, because this way can lead to a better understanding of Chinese culture, and otherwise the getting-to-know process may be humdrum and rigid. Here we utilize Guandong culture area as a detailed example of Chinese regional cultural image, through the introduction of the differences and common characters of Heilongjiang Province, Jilin Province and Liaoning Province.

Paramedics and Emergency Medical Technicians (EMTs) often serve dual roles in their communities as both emergency medical providers and firefighters. Therefore, the demands and needs of these providers are different than those working directly in a hospital emergency room or medical office. Medics are required to treat a patient in less than ideal conditions where seconds can mean the difference between life and death. The goal of this work is to better understand how research informing technology for the emergency room (ER) can be linked to improving the user experience of EMTs and paramedics in the field. Through a review of relevant literature, we capture lessons learned in conveying information quickly, linking necessary information from disparate sources, and giving these providers accurate information to successfully treat and transport patients during prehospital care.

Currently, computing education, especially programming education has become more important. Meanwhile, programming education has many difficulties such as should learn many concepts and skills. Researches of Intelligent Tutoring System (ITSs) have been attempted to reduce these difficulties. ITSs are educational systems that able to adaptively pedagogical behavior and feedback and aim to supply adaptive tutoring to learner’s profiles by alternate to human tutors. Despite there are much supports to programming education by ITSs, there no attempts for organizing knowledge in programming. Organizing knowledge is acquiring the systematized knowledge and its scalability which enabling to existing knowledge reuse to the same or similar problems that solved once by scaling knowledge. We considered that organizing knowledge is fosters problem-solving skills, and it gains Computational Thinking eventually. Therefore, we have been focused on supporting the process of solving problems by combining a bit of program. Then we selected the knowledge of “function” and “source program that achieves the function” as knowledge to be organized. And, we defined a pair of knowledge as a component. In this paper, we proposed and developed Compogram: an ITS for organizing knowledge by visualizing behavior in programming. Furthermore, for identifying learning gains, we conducted an evaluation compared to our conventional systems. Results were suggested that Compogram was fostering knowledge organizing skills that can apply to out of learning ranges.

For the Chinese, Zongzi is a kind of food that often appears in our daily life. However, with the development of modern automation technology, the original hand-washed leaves were also cleaned by machines. As time experience accumulates, some of the problems that users find will help to improve the efficiency and cleaning effectiveness of the Zongzi leaves cleaning machine, which is worthy of further study.Generally, it takes many steps to clean the leaves, which is quite time-consuming. Cleaning requires brushing back and forth to remove sand or bug eggs on the leaves. Because of the different thickness of the leaves, it is more likely to cause damage to the general machine, which greatly increases the cost. This study hopes to improve the problem and use the design of the human-machine interface to complete the development and design of the new machine.This study used an in-depth interview to investigate the needs of the industry. Then, by the Systems engineering and User-centered design, the problems can be classified into four categories: filtering, cleaning, storage, and others. And for each function, find the suitable requirements and appropriate mechanism to design.The results are suitable for small and medium-sized food factories, it can efficiently and quickly clean the Zongzi leaves and make consumers feel at ease eating.

The technology of computer graphics (CG) has been rapidly developing, and is being utilized in various domains. Driving simulators (DSs) can provide driving experience to a user/driver by reproducing a virtual traffic environment using CG. In recent years, advanced driver-assistance systems have been actively researched, developed, and evaluated by automobile companies and ministries that hold the jurisdictions of transportation. Accordingly, the need to use DSs has become strong as they are being used instead of real vehicles. However, the subjective speed for driving a DS is lower than that for driving a real vehicle. Consequently, in the case of DSs, some participants aggressively drive at fairly high speeds, and thus some data collected from DSs become unreliable. Therefore, to increase the fidelity of the driver’s behavior, a major challenge is to improve the subjective speed while using a DS to match the subjective speed in real driving. Two mainstream approaches employed to improve the subjective speed when using a DS are to spread the areas that display the images and to introduce a motion-based system. However, these approaches increase costs and require large space. In a previous study, the subjective speed was improved by correcting the CG image without the problems of high costs and large space. In this study, the objective is to control the subjective speed using CG image correction.

The final goal of this study is to elucidate the contribution of haptics and vision to the Sense of embodiment (SoE) in a virtual reality (VR) environment through physiological behavioral measurements. To achieve the objective, a rod-tracking task was employed in which a rod held in the hand is passed along a sinusoidal path in VR environment using HMD and haptic device. The problems identified in the previous system were the device positional accuracy and insufficiency of the force sensation. In order to solve these problems, the control circuit of the haptic device was modified. Then, the positional accuracy of the device and the force output characteristics of the device were evaluated. Through these evaluations, it was confirmed that the accuracy of the device was improved, and the strength of the force presentation was improved. In addition, we evaluated the experimental environment by measuring physiological behavior. The evaluation of the experimental environment by the physiological behavioral measurements was carried out by a questionnaire survey on the Rod Tracking Task, which included measurements of muscle potential and subjective evaluation. In the future, we will improve the accuracy of the device, improve the control circuit, and change the force-sensing model in consideration of the system construction.

This paper explores various factors linked to social media use and its effect on the socio political realm of Ethiopia, which currently is a nation under political reform. Social media tools such as Facebook, Twitter and Telegram were extensively used by opposition movements that toppled the dictatorial regime that ruled the nation for over 27 years. While this is the positive side, currently ethnic extremist groups and different political factions are using social media to instigate violence and genocide that displaced millions of people across the nine Ethiopian regional states. In view of quelling the sporadically erupting ethnic violence, the Ethiopian government frequently disrupts Internet connections. This has caused untold distrust across hundreds of the diplomatic entities the nation hosts and among the business and scientific communities. The intermittently occurring political unrest as a result of fake news and hate speeches circulating through social media, has led the general public to develop negative impressions with regard to social media and Internet technologies. Further, the misuse of the technology is also urging the government to rethink its free use and is resorting to device protective measures. This study intends to explore the fortunes and caveats brought about by social media in the Ethiopian socio political life and propose mechanisms that would foster appropriate use of the technology. Data for the study was generated via focused group discussion and document review. The study revealed technical, legal, and ethical mechanisms surrounding social media use in the context of Ethiopia.

This paper focuses on infodemic response using semi-automated application, seeking to curtail the misinformation of COVID-19 related news and support reliable information dissemination in Ethiopia. We analyze the emerging news trend about COVID-19 in selected social media sites (Facebook and Twitter) and Language (Amharic/English) using the information extraction tool that we developed. This web-crawling tool extracts posts and tweets that have larger audience, high engagement and reaction in Ethiopian popular social media pages and profiles. Expert fact-checkers (group of three to five experts) are then used to verify the veracity and correctness of each of the selected posts/tweets. Posts and tweets are selected based on the keyword patterns emerged from the analysis. The system will present a dashboard to the experts with the required information to label the news as misinformation and educative (opted two broad categories) decided at this stage. The verified news and information will be pushed to various social-media sites, conventional media and to our COVID-19 related information dissemination website. This will provide counter-information with better evidence and proactively flag misinformation and disinformation, and furthermore convey accurate and timely information as educative. This can be achieved through three phase (problem identification, solution design and evaluation) design science approach by emphasizing the connection between knowledge and practice.

University planning requires a set of processes for continuous quality improvement but is often hampered due to the lack of project management across higher education. This paper discusses the benefits of carrying out continuous client feedback and communication processes throughout the lifecycle of information technology projects in higher education to assess and evaluate the condition of a project. The discussion includes the impact of customer participation on IT project performance as part of project quality management. Research shows that quality communication between stakeholders and project team members results in fewer misunderstandings and more precise definitions; however, there is a literature gap when it comes to assessing IT projects within higher education. Confirming expectations to improve customer perceptions of the project process and performance has a positive effect on client satisfaction. The paper emphasizes the importance of transparency on the part of IT in higher education project work, particularly in public universities, by involving higher education staff in all phases of the project, from project prioritization and selection to analysis, design, and implementation of the solution. Best practices for assessment and improving project outcomes are offered, as well as managing project quality and information flow. Future research directions are also offered.

The impacts of advertising-disclosure language on influencer marketing have increasingly attracted researchers’ attention. However, little research has focused on the role of pictorial types on social media influencers and brands. Thus, this study explores how different combinations of advertising-disclosure conditions and pictorial types can affect social media influencer credibility and consumers’ brand attitudes. By using an experimental 3 × 2 between-subject design, we collected data from 264 followers of beauty influencers on Weibo. Results revealed that a post that disclosed sponsorship significantly decreased influencer credibility and consumers’ brand attitudes compared to a post without any disclosure. Results also showed that a post with no-sponsorship disclosure significantly increased influencer credibility and consumers’ brand attitudes than a post without any disclosure or a post disclosing sponsorship. With regard to pictorial types, the influencer-with-product type led to higher influencer credibility and more positive brand attitudes in consumers than the product-only type in all three disclosure conditions. This study highlights the role of pictorial types in strengthening the power of advertising-disclosure language, which can further affect influencer credibility and consumers’ brand attitudes. This study contributes to the visual complexity literature for influencer marketing.

Anxiety disorders are closely associated with an individual’s interactions, manifested in the way an individual expresses themselves and interacts with others in their social environment. However, little is explored empirically about the association of social network structure and the interactions of an individual with aspects of mental health functioning, such as anxiety. In recent years, individuals have begun to appropriate social media to self-disclose about their mental illnesses, seek support, and derive therapeutic benefits. The study examines the online social network and interaction characteristics of Twitter users who self-disclose about their anxiety disorders. We analyze a sample of 200 Twitter users and their over 200,000 posts shared on the platform, who were expert-validated to have self-disclosed about suffering from an anxiety disorder. On their data, a variety of attributes of the users’ online social networks, interactions, and social behaviors using natural language and network analysis approaches were modeled using state-of-the-art network science measures. A number of state-of-the-art supervised learning classification frameworks are built using these attributes, to identify whether an individual’s anxiety disorder status could be automatically inferred. Results show that these social network, behavior, and interaction attributes, when incorporated in a support vector machine classifier, signal an individual’s self-reported anxiety disorder status, in contrast to a demographically and activity matched control group, with 79% accuracy and 84% area under the receiver-operating characteristic curve. The work provides the first insights into the role that the social interactions and social network structure on online platforms play in characterizing an individual’s mental health experience, such as anxiety. We discuss the implications of our work in instrumenting online social platforms in ways that yield positive affordances and outcomes for individuals vulnerable to mental illnesses.

This article aims to be a reflection, an analysis and a return to the reader of the path of conception and implementation of a communication campaign against gender violence. The project has been developed at the Inter-University Research Centre “Gender Cultures” in Milan, and wants to contribute and to give substance to the Istanbul Convention, which in its article 13 states that “to promote or implement awareness campaigns or programs (…) to increase awareness and understanding by the general public of the various manifestations of all forms of violence (…) as well as the need to prevent them”.To this end, three Italian and Milanese universities have been involved and a specific methodology has been used that has highlighted, from a communicative point of view, some important innovations. A group of university students, previously trained, carried out the creative work for the awareness campaigns by dividing themselves into subgroups and structuring a campaign in which the language was completely internal to the subculture of reference. Not only because the social segment to which the communication producers belonged was in fact homogeneous in terms of lifestyles, beliefs and/or worldview to the social and cultural segment of the campaign’s target, but also because they were inspired by tales of violence experienced by other students at the Milanese universities. Another element of solid novelty concerns the field research carried out with neuromarketing techniques on a representative and very small sample of the reference universe.

Blockchain systems promise to fundamentally transform the way users interact with systems of governance, finance, and administration. Since relevant changes are expected to appear on a global scale, considerable methodological challenges exist regarding the sound description and adequate design-theoretic conceptualisation of respective social transformations. Artificial societies are a proven method for exploring the dynamics of large scale social systems which are otherwise hard to observe. They allow for precise modelling of social processes, facilitating an experimental attitude towards large scale systems which otherwise remain inaccessible to researchers. Within this paper, we describe how artificial societies can be employed as part of a practice-based research strategy aimed at elucidating a large scale transformation of this kind: the role of trust within social practices facilitated by Blockchain technologies.

Each new type of graphical icon (graphicon) in CMC has been more complex and multimodal than its predecessor. For this reason, and because of their novelty, Konrad, Herring, and Choi (2020) claim that new graphicon types are initially restricted to use in intimate relationships. We explore this proposition qualitatively by interviewing student users of Animoji – dynamic, large-scale emoji on the Apple iPhone – about who they send Animoji messages to and why. The results of a think-aloud card sort task in which participants (N = 33) matched seven Animoji with seven relationship categories at different social distances and sent a message to each one were triangulated with responses to open-ended questions before and after the task. Participants sent Animoji to close friends, significant others, and siblings, and to a lesser extent, parents and other family members. They rejected the idea of sending Animoji to more distant relationships such as a teaching assistant, a mentor, and new friends. Different Animoji were considered more or less suitable for each relationship, as well as for recipients of different genders. The reasons given by the interviewees for sending Animoji to each relationship category centered around themes of politeness, (in)formality, familiarity, and self-presentation.

Ecommerce livestreaming, also known as live commerce or social commerce, has taken off over the past two years in East Asia and is showing the tendency of going global. Intrigued by the phenomenal success of ecommerce livestream, we concentrate on analyzing the most prominent and illustrative example of Chinese ecommerce live-streamer Austin Li. Through this individual case study, we aim to investigate discursive strategies employed in ecommerce livestreaming and reveal resources specific to this new media genre. Guided by multimodal discourse analysis, our research first accommodates the socio-economic context of Li’s success to warrant social situatedness in interpreting data. After that we move into analyzing his discourse employed in livestreaming. Research findings suggest that in attention economy, Li strategically utilizes his male gender as a resource in trying on lipsticks for female customers. His discourse in multiple modes serves to build consumer trust and propagate products. An in-depth analysis of his discursive strategies indicates that, ecommerce livestreaming as a new form of advertising not only shares commonalities with traditional advertisement discourse but also embodies affordances that are specific to livestreaming platforms. To be more specific, livestreaming is featured with delimitation of time, real-time interactivity, and video-aided communication. These affordances enable Li to adopt more interactive and personalized persuasive discourse than conventional advertisements.

Many surely dream of being able to chat with his/her favorite anime characters from an early age. To make such a dream possible, we propose an efficient method for constructing a system that enables users to text chat with existing anime characters. We tackled two research problems to generate verbal and nonverbal behaviors for a text-chat agent system of an existing character. In the generation of verbal behavior, it is a major issue to be able to generate utterance text that reflects the personality of existing characters in response to any user questions. For this problem, we propose the use role play-based question-answering to efficiently collect high-quality paired data of user’s questions and system’s answers reflecting the personality of an anime character. We also propose a new utterance generation method that uses a neural translation model with the collected data. Rich and natural expressions of nonverbal behavior greatly enhance the appeal of agent systems. However, not all existing anime characters move as naturally and as diversely as humans. Therefore, we propose a method that can automatically generate whole-body motion from spoken text in order to make it so that anime characters have human-like and natural movements. In addition to these movements, we try to add a small amount of characteristic movement on a rule basis to reflect personality. We created a text-dialogue agent system of a popular existing anime character using our proposed generation methods. As a result of a subjective evaluation of the implemented system, our models for generating verbal and nonverbal behavior improved the impression of the agent’s responsiveness and reflected the personality of the character. In addition, generating characteristic motions with a small amount of on the basis of heuristic rules was not effective, but rather the character generated by our generation model that reflects the average motion of persons had more personality. Therefore, our proposed methods for generating verbal and nonverbal behaviors and the construction method will greatly contribute to the realization of text-dialogue-agent systems of existing characters.

Recently, computer-supported interactive technologies have played a significant role as complementary tools in creation of extraordinary artworks. These technologies have been used in art to explore their utility to compose new creative concepts, and to enrich the dimensions of artistic performances to strengthen the engagement between the performer and the audience. Since integrating the audience into the artistic performance has a significant role in enhancing an individual pleasure, a robotic medium holds great potential in bringing about new opportunities for artistic performances. In this preliminary study, we observed the effects of eye gazing behaviours of a minimal robot on audience engagement and connectedness in regard to an artistic performance. With this paper, the results from the data of a limited number of participants show that the audience tended to be distracted by the robot’s existence, however, the gazing behavior of the robot maintain a feeling of connectivity between the robot and the audience.

In the modeling of impressions, a key factor for success is to extract nonverbal features that can be used to infer the target variable. To extract the effective features for capturing the relationship between the target subject which has the personality trait and other group members, Okada et al. propose a co-occurrence event-mining framework to explicitly extract the inter-modal and inter-personal features from multimodal interaction data. The framework is an unsupervised feature extraction algorithm by considering the relationship between nonverbal patterns of the target subject and group members. Though the label data of personality trait is useful to improve the accuracy, the valuable label data is not used for feature extraction. In this paper, we enhance the inter-modal and inter person feature extraction algorithm by using a deep neural network. We proposed a representation learning algorithm for capturing inter-modal and inter-person relationships by integrating using a convolutional neural network (CNN). In the experiment, we evaluate the effectiveness of the representation learning approach using the ELEA (Emerging Leadership Analysis) corpus, which includes 27 group interactions and is publicly available. We show that the proposed algorithm with CNN slightly improves the personality trait classification accuracy of the previous algorithms. In addition, we analyze which slice of multimodal time-series data is key descriptors to predict the personality trait using the proposed algorithm with CNN.

Eye movements are important but, in Japan, not tested so. However, there are some reports that training eye movement can improve developmental and learning disorders. In the U.S. or EU countries, these tests and training are generally performed as medical procedures by optometrists. But these depend on their experience and knowhow. In this study, we develop an eye movement training system using a gaming eye tracker. First, we proposed a calibration method to realize highly precise eye tracking during training. Next, we developed a prototype of an eye movement training system. Then, we measured and analyzed the data of eye movements, and proposed some parameters with individual differences and high reliability for the test and the analysis of the effects of training. The results of the experiment demonstrated effectiveness of the system.

YouTube is able to generate new forms of user interactions and an entire evolutionary cycle in audiovisual languages and digital culture through the interface. This platform offers the possibility for the user to assume the functions of prosumer of audiovisual contents, through generating their own digital identities. In this way they are able to influence and be part of the society of production, diffusion and audiovisual user interactions. The main aim of this research was to obtain a general idea and a first approximation of the tendencies of audiovisual popular user interactions and the digital culture on YouTube, which was undertaken by means of the quantitative analysis of YouTube video interfaces selected by YouTube categories. In order to extract this information, a quantitative analysis of the most viewed channels and videos was undertaken. These interface categories were those with more views, with more subscribers, with more likes and dislikes, with more comments, as well as the average time of some of the most viewed videos. This was done through a sample of 160 most viewed videos of the platform. The aim was to understand the common denominators and interface preferences that users manifest through their interactions with videos, channels and thematic categories in the YouTube digital culture interface. The conclusion from the study was that the YouTube categories that enjoy the most popularity are education and music, at the same time the interaction features of each category can also be defined on the YouTube platform.

There has been an increase in both wearable devices and social media usage. This study sets to describe how social media influences the buying intentions of Wearable Devices (WD). In doing so, constructs from Information Acceptance Model (IACM) had been compared to the resulting themes from 9 one-on-one interview responses and a relationship between social media and wearable devices was formed.Objectives: Primary objectives were to determine the relationship between social media and; (i) WD sales, (ii) WD features and application information (iii) ongoing interactions on WD’s.Secondary objectives were to determine (i) if the availability of a WD affected the volume of social media interactions and (ii) if the value associated with a WD was related to the social media posts of that device.Design, Methodology, and Approach: This study took a qualitative approach to research and used phenomenology as a stance of exploring social media’s influence on purchase intentions towards the wearable device. A positivist philosophical standpoint was applied to deduce themes from the ICAM by touching on interpretivism elements in analyzing the data collected from semi-structured interviews. The data was then categorized into themes, refined into sub-themes and then assessed according to the research propositions as well as the ICAM frameworks constructs.Findings: Social media was viewed more of as an information outlet as opposed to a driver of purchase intention. From this, it was seen that word of mouth was the biggest driver in WD awareness. Information Quality, Attitudes towards information were the main influencers that social media has towards purchase intention from the ICAM model. This was evident in the construct scores which showed that there was a relationship between the adoption of social media information and purchase intention, that there is a relationship between the features of a WD and social media usage as well as showing that there is a relationship between the users’ perception of the type of social media platform and the WD presented on that platform.Research Implications: This study explored the influence of social media on the buying intention of wearable devices as well as provided channels for further exploratory research into the human perceptions of information provided on social media.

The Internet has changed the way people, organizations and institutions communicate. Accordingly, advertising planning is undergoing a dramatic change from traditional ATL communication tools such as newspapers and magazines to non-traditional BTL tools such as mobile and Internet marketing.Marketers can use online advertising to build their brands or to attract visitors to their Web sites. Online advertising can be described as advertising that appears while customers are surfing the Web, including banner and ticker ads, interstitials, skyscrapers, and other forms.An effective advertising strategy for online advertising aims at targeting the right advertisement message to the right person at the right time.

The aim of the paper is to define design recommendations for gender- and diversity-sensitive social media appearances to strengthen participation in the context of local public transport and mobility planning. Social media are an effective instrument for actively and sustainably involving citizens and other interest groups in planning and evaluation processes [1]. A major advantage is its reach across gender, cultural, language and national boundaries, which means that a high diversity of users can be covered. For this very reason, social media have become one of the most important tools when it comes to implementing and promoting participation culture effectively and efficiently. Social media can not only be used to inform interested parties, but also to actively and above all interactively involve them. In order for this to happen, the needs and requirements of users must be taken into account when designing social media appearances. In addition to flexible user interface design and content design, this includes enabling and providing elements for an interactive exchange of information, opinions and experiences between providers and users as well as among users. Although this type of participation is already widespread (e.g. as marketing for companies and products, but also for political opinion-forming), it has not yet fully entered all areas. Especially in the transport sector, the social media appearances provide information, but often these are not designed to be gender- and diversity-transcending and therefore not understandable and usable for all target groups. Every day, countless and diverse people are moved and connected with each other over long distances via public transport, but this user diversity is not addressed and reflected on the social media appearances of public transport companies.

Emotion plays a vital role in social interaction. Often, the speaker’s attitude is as essential as, if not more important than, his/her words for communication purposes. In this paper, we present experiments for using conversational context to help text-based emotion detection. We used data from the Dialogue Emotion Recognition Challenge – EmotionX. BERT is used for encoding the input sentences. We explore four ways for encoding the input by varying whether to concatenate a dialogue history with the current sentence and whether to add the speaker’s name as part of the input. Our results indicate that adding context can improve the results of emotion detection when the emotion categories do not overlap with each other.

This study introduces a new instrument for leadership evaluation in online forums and other online communities which was developed using a grounded approach. Questions that emerged from the literature were then evaluated to create hypotheses that guided the development of an instrument for moderator evaluation. The Moderator Evaluation Contingency Scale (MECS) is modified from Fiedler’s contingency model to determine if a moderator is more task- or relationship-oriented in his or her approach to moderation and interactions with other members of a community. The MECS was developed and tested on Reddit in 2013–2014 using random sampling for Forum selection, moderator selection, and interactions with users. A content analysis using the MECS to evaluate posts was found to be a viable measure of a moderator’s ability to perform tasks like removing content as well as his or her ability to interact with users. Bots were analyzed using the MECS as well to determine bias. Next steps include making the instrument available for use by social media and niche community sites, administrators, and other moderators.

It has been suggested that neuro-diverse individuals may be particularly good at detecting online deception (Pick 2019). A small-scale exploratory study was conducted to investigate whether individuals with traits associated with Autism Spectrum Disorder (ASD) were more or less accurate in spotting different types of fake news. A non-clinical sample of university students completed an online identification task, where both fake and real articles items were manipulated in terms of their emotive content. When individuals with low and high scores on the Autism-Spectrum Quotient (Baron-Cohen et al. 2001) were compared, there were no significant main effects on detection accuracy. However, there were two significant interactions, indicating an interesting relationship between message emotiveness, ASD and fake news detection. The results contribute to an understanding of how psychological differences, in particular ASD, may affect online judgements and will contribute to a developing body of work relating positive skills of neuro-diverse individuals to the cybersecurity industry.

In the age of web 2.0, the concept of “the User Generated Content (UGC)” is put forward. Now millions of images posted on the photo-sharing service such as Instagram. In this paper, we choose the popular photos “follow me to” on Instagram as an example for analysis. By utilizing the comparative analysis of the “follow me to" photos of the photographer and the imitators, we explored the pattern of image propagation on Instagram and the characteristic of the popular images. In this paper, we also established a research method by content analysis and image analysis based on the image itself to study social media.

Over the past few years, mobile commerce (M-commerce), which is a new channel for conducting online businesses has revolutionized the global market. In Qatar, due to lack of trust, an only small percentage of Qatari populations has shown an interest in mobile shopping although the average annual individual’s expenditure is impressive. Therefore, it is crucial to investigate antecedents of consumer’ trust in the context of mobile commerce [1]. The objective of this paper is to explore whether trust perceptions towards mobile shopping among diverse segments of consumers living in Qatar vary significantly or not by proposing a conceptual framework for trust based on the Technology Acceptance Model. An online survey was conducted to empirically validate the newly developed trust factors between consumers with different nationalities, genders, and age ranges by performing permutations and partial lease squares multi-group analysis algorithms. Our research findings revealed that nationalities differences related to the factor perceived usability had positive indirect effect on Qataris trust, female consumers’ trust could be enhanced by perceived usability, and young consumers could easily trust mobile commerce via the endorsement of social media influencers. The results also emphasized that perceived security was one of the most significant factors that affect drastically mobile commerce trust between all groups of consumers. We ended our work offering some valuable theoretical implications for scholars and interesting strategies for practitioners to help to create customer’s trust especially during crises, such as COVID-19.

Companies are exposed to the risk of falling victim to cyber attacks every day and therefore invest in optimizing their information security (IS) level. In addition to technological investments, the focus is now increasingly on employees, as their attitude and behavior has a significant influence on the IS level of a company. There is already extensive research on the influencing factors and the establishment of an IS culture in companies. However, little attention has been paid to the group of IT employees, although it has been proven that their attitude, behavior and judgment regarding cyber attacks and IS in general differ from non-IT employees. Even within an IT department, one can expect to see different degrees of these factors, as a distinction must be made between IS employees and employees with traditional IT functions (software development, server operation, etc.).Based on 25 recent IS studies, a literature review has identified four factors that influence the IS attitude and behavior of employees in an internal IT department and thus have an impact on the IS culture. These four components are IT tools, IS skill, appreciation and sub-cultures.The results show that more qualitative research with a focus on employees of an IT department is necessary to advance the findings in the area of IS culture. In addition, CIOs and CISOs benefit from the results, as they specify fields of action that can be tested and optimized in their own organizations.

Different from traditional services, online services can simply develop from the place of origin to any region of the world. However, users in different regions are mostly used to local service design. Therefore, when online services are developed in different regions, service designers should consider that users have different perceptions of user experience. In this study, the rapid development of shared bikes around the world is used as a reference object. By comparing the different payment systems of online Share Cycle services between China and Japan, investigate the reasons, and research on User Experience of the Payment System (include Pre-charge or Post Payment, Manual Payment or Automatic Payment etc.) by questionnaire survey. In the subsequent research, I hope to propose user experience and service design methods that can be applied to China and Japan.

Logistics is increasingly essential for the economy and social development. Statistics show incremental contributions in GDP, job creation, and in the movement of goods worldwide, connecting suppliers with companies and distributors and stimulating different economic sectors of manufacturing and services. However, the challenges of the logistics sector include optimizing its operations, reducing costs, and generating an offer of services with added values for its clients and interest groups. In this sense, innovation and management systems can support companies in the sector in the search for competitive advantages and operational efficiency aligned with corporate strategy and the environment. Different models and methodologies have been developed to work in an integrated way on innovation processes and management systems, with a focus on continuous improvement where evaluation and development are crucial to identifying the level of performance, gaps, and improvement strategies. Besides, the use of multi-criteria decision methodologies was identified in the scientific literature as an objective approach and easy to implement in companies, but of little application in the evaluation of innovation and the integration of management systems for the logistics sector. This paper presents the application of a combined multi-criteria decision-making methodology to evaluate the innovation process in conjunction with the integration of management systems used in the logistics sector. First, the Analytic Hierarchy Process AHP is applied to determine the weights of each criterion and sub-criterion through qualitative pair comparisons. Then, The Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) is used to evaluate three big companies of the logistic sector considering their ability to develop the process of innovation under criteria associated with Integrated Management Systems (Quality, Environmental, Health, and Safety). A case study is presented to validate the combined approach.

Nowadays, due to the huge volume of information available on the web, the need for personalization is more than necessary. Choosing the right information for each user is as important as the way this information is presented to him or her. Currently, user-triggered recommendation requests for web services are implemented as an automatic recommendation based on parametric computation. This work reports on a specialized user interface for business processes, where writing code entails invocation of business process information. The paper presents the user interface design for Personalized Web Service Selection in Business Process scenario execution and the user evaluation by business process engineers.

Social networks have become a widely used way to share information, including images. This information can be useful for companies, which need to know their customers’ opinions and their interest in their brands. For these purposes, an image classifier has a great utility. Currently, deep learning using convolutional neural networks are heavily employed for image classification. However, they require a large number of training image samples, which are not always accessible. In order to solve this problem, we can use data augmentation, which is a regularization technique that is based on expand the original dataset to increase classification accuracy and avoid overfitting. This present work aims to compare the use of different data augmentation methods for brand logo classification. For tests, seven methods (flip, crop, rotation, gaussian filter, gaussian noise, scale, and shear) were selected based on previous studies. Two convolutional neural networks were used, AlexNet and SmallerVGGNet, this way we could see if some combinations lead to better results in different artificial network architectures. Ten different combinations of those methods show that the combination of flip, crop, rotation, and scale is a more effective combination for a brand logo classifier in the both convolutional neural networks used, improving accuracy by 22.09% using AlexNet and 12.57% using SmallerVGGNet. Other good results are found with the combination of all seven methods; flip, crop, rotation, plus gaussian noise; and the combination of flip, crop, and rotation. Further research is intended to use another regularization technique along with data augmentation to improve even more the accuracy and reduce overfitting.

COVID-19 has disrupted our lives and the economy. In this paper, we outline approaches in which information technology can be used to implement business strategies to enhance resilience by coping with, adapting to, and recovering from adversity resulting from the COVID-19 pandemic. We discuss how information technology such as digital supply chain, data analytics, artificial intelligence, machine learning, robotics, digital commerce, and Internet of Things can be used to enhance resilience and continuity of business.

In this decade, it is not necessary to have technical knowledge for the investment since the automatic algorithms to sell/buy investment destination have been developed with artificial intelligence (AI). In our previous study, measuring similarity (stationarity, fractality, and degree of determinism) of variations in the exchange rates to the pseudo-exchange rates generated by Generative Adversarial Networks (GANs), we compared Winner processes with the GANs. From the viewpoint of stationarity, the similarity of sequences in the pseudo exchange rates were higher than those generated by the Winner processes, and high scores in the similarity were resulted from both sequences in terms of degree of determinism. In this study, we have applied this AI system to numerical simulations of the stabilogram whose randomness is remarkably greater than that of the other bio-signal in accordance with the nonlinear analysis.

The smartphone penetration in India is growing rapidly and online buying through mobile apps for products and services is growing at a faster pace. Restaurants in brick and mortar format in order to increase their customer base are trying to get their feet wet in an online mode. Though India has attracted food tech companies due to majority of population being millennial consumers, not many studies have focused on consumer behavior towards online food delivery and ordering through mobile apps especially pertaining to students’ market. Hence this study in an initiative to study the effect of mobile app design features on decision making stages of consumers pertaining for online food ordering and delivery sector. The study adopted SEM analysis through Smart PLS-3 with sample being students studying in Manipal Academy of Higher Education campus from across the globe. The result of study reveals that design features of mobile apps has huge impact on the students’ behavior design, with features, namely, ‘‘Security towards the retention of personal information of students’’, ‘‘Secure and accessible payment gateways”, “Option of tracking real time order status of food and beverages ordered”, ‘‘Access to customer service to respond to customers query without any hindrances”, ‘‘Pop up of trending information of food and beverages”, “Easy navigation of app features”, ‘‘Search function to quickly access the information”, and ‘‘Delivery services which are flexible”. This study could be used as a base by organizations to enhance the design features of mobile apps in food ordering sector for engaging customers and enhancing their business.

In recent years children are one of the biggest consumers. Many industries are targeting children to sell their products. Many individuals are creating full-time content for the kids. Children are attached to screen watching cartoons or playing games. There are many educational contents. After watching more content on the digital device, children’s behaviors change dramatically. They become more stubborn. They become angry and addicted to digital materials. Industries are creating more content to attract kids. But those contents make the children addicted. It is a big question about the intention of the sector. The E-commerce sector has boomed targeting, especially children, and spending thousands of dollars to reach the kids. Many platforms have risen, such as paid services for the children. Absent parents are happy to leave the kids to the digital device as the devices keep the kids happier. But it is a big question that how much helpful those digital content for children.

Sleepiness that can arise from sleep deprivation can increase human errors in task performance and create workplace hazards and accidents. Hence, it is critical to detect sleepiness to minimize hazards and human errors. This paper provides a review of the literature on eye tracking metrics that can be used to detect sleepiness. These metrics include blink duration, blink frequency, saccade latency, saccade peak velocity, saccade accuracy, smooth pursuit velocity gain, fixation rate, pupil size, and latency to pupil constriction.

Industry 4.0 (I4.0) is characterized by cyber physical systems (CFS) and connectivity, paving the way to an end-to-end value chain, using Internet of Things (IoT) platforms supported on a decentralized intelligence in manufacturing processes. In such environments, large amounts of data are produced and there is an urgent need for organizations to take advantage of this data, otherwise its value may be lost. Data needs to be treated to produce consistent and valuable information to support decision-making. In the context of a manufacturing industry, both data analysis and visualization methods can drastically improve understanding of what is being done on the shop floor, enabling easier decision-making, ultimately reducing resources and costs. Visualization and storytelling are powerful ways to take advantage of human visual and cognitive capacities to simplify the business universe. This paper addresses the concept of “Storytelling with Data” and presents an example carried out in the shop floor of a chemical industry company meant to produce a real-time story about the data gathered from one of the manufacturing cells. The result was a streaming dashboard implemented using Microsoft Power BI.

Compared to traditional sales model, influencer marketing motivates consumers in a totally different way in this era of mobile phone. This type of marketing uses various phenomenons hot online, such as a delicately designed image with high attention, so targeted merchandise can be concerned associatedly. The way which influencer marketing uses activates consumers’ interests and improves the appeal of products. The success of influencer marketing also indicates the achievement of mobile communication and motivates my study.Kansei Engineering was applied to study how influencer marketing can motivate consumer through mobile communication based on human emotions. Hence, EGM (Evaluation Grid Method) was used to determine the interdependent appeal factors and specific characteristics of influencer marketing based on experts’ opinion. In addition, this study took advantage of Quantification Theory Type I to analyze the importance of each appeal factors and characteristics according to consumers’ responses. This study combined in-depth interviews and questionnaire surveys, and can be individual analyzed through EGM and Quantification Theory Type I. Hence, both experts’ and consumers’ preferences to influencer marketing can be reveal. Then, the role of mobile phone can be positioned and clarified in influencer marketing & communication based on the results of this study.The semantic structure of appeal of influencer marketing, as the results of EGM analysis, showed the hierarchy of the relationship among appeal factors, the reasons for consumers’ preferences, and the specific characteristics. In addition, the results of Quantification Theory Type I analysis indicated that appeal factors will be affected in varying degrees by particular reasons and characteristics in this study. Then, the influencer marketing strategies could be used for mobile communication on the basis of the result of this study. Researchers who are concerned about the issues of influencer marketing can get useful information in this study. Furthermore, the achievements of this study can contribute to the field of marketing, mobile communication, social media, and media design.

The online advertisements (ads) with presence design are widely proved to be more appealing for attracting users’ attention. However, the different visual processing mechanism towards presence design and consumers’ involvement has not been well investigated. This study combined subjective evaluation with eye-tracking data to investigate the effect of consumers’ involvement on their visual attention to online ads with different sense of presence. Refined and re-calibrated presence scale and approaching-avoidance trend scale were constructed to respectively measure consumers’ perceived sense of presence and behavioral intention to online ads. Two tasks were designed to simulate different sense of user involvement. In task one, participants just freely browsed two banner ads. Meanwhile binary choices were used in task two to ask participants to select one with higher purchase intention from two vertical search ads and then click the mouse. Both tasks were completed by each participant whose eye movement data was recorded by an eye-tracker. The perceived sense of presence and corresponding behavioral intention of each two ads were evaluated after each task. The results showed that online ads with high presence will significantly increase consumers’ fixation counts, revisit counts, saccadic counts, blink counts in browsing-driven task which will significantly improve consumers’ stickiness. As to purchasing-driven task, however, online ads with high presence will reduce fixation counts, saccadic counts, blink counts which indicates that the online ads with high sense of presence can reduce the difficulty of information extraction, thus helping the customer to make purchase decisions effectively.

The present study advances a new conceptual framework explaining and predicting individual resistance to information systems (IS). IS Resistance depends on how individual users perceive the implementation process, its outcome and their relationship with the managers and implementers of the system. We draw on the justice literature to conceptualize the characteristics of the implementation process and its expected outcomes, and from the trust literature to conceptualize the relationships between the users and their managers. In addition to the concept of distributive justice that refers to an individual’s perceptions about the expected outcomes of an IS implementation process, our model includes the constructs of procedural justice, interpersonal justice, and informational justice to capture different aspects of the interaction between the users, the managers and the implementers. In line with previous conceptualizations developed in the justice literature, we also propose that trustworthiness towards managers and implementers will mediate the effect of procedural justice and interpersonal Justice on individual intention to resist an IS. We conclude with a discussion about the theoretical and practice related contributions to the HCI and IS fields.

Most people have to work from home (WFH) due to stay-at-home orders in response to COVID-19 pandemic. The shifting of work environment from regular office to home has caused changes in workload and productivity, which may lead to reduced salaries for employees, economic loss of the companies, and impacts on the national economy. Thus, it is urgent to explore the impacts of WFH on workload and productivity of different employees. A nationwide survey was distributed to collect data about the workload and productivity of regular work and WFH considering different types of tasks and occupations. The findings indicate that WFH causes an increase in workload for all participants by three hours per week and a loss of productivity for 38% participants. Moreover, the technical issues, such as less efficiency of online communication technologies, are the core reasons for the decrease in productivity. For different occupations, employees who regularly work in an office or workstation show a higher workload because their major work can be done at home but require more time due to the technical issues, while on-site occupations and many researchers have less workload because their major work cannot be done at home, such as onsite work and experiments. Then, the workload and complexity of tasks lead to the differences in productivity. In the future, the key problems are how to address the technical issues and strengthen the human-computer interaction to improve the productivity, and support on-site work and lab-based tasks to improve the feasibility of WFH.

The accounting and finance industries have been increasingly adopting new technologies in recent years. In this exploratory study, we examine the degree of technology awareness in the accounting and finance industries over the past ten years. By identifying all the twitter accounts of the top 100 accounting firms and top 100 finance institutions and examining how they have discussed about technologies. We are able to conduct a series of analyses to help the audience gain a better understanding of the patterns and changes of technology awareness in the accounting and finance industries.

With flow dividend of traditional e-commerce is diminishing gradually, the growth rate of e-commerce users is slowing down, the major e-commerce platforms are in great need of content innovation and new flow portals. E-commerce live streaming has become one of the breakthroughs for the platforms. Its growth prospects depend on whether the live streaming users can turn into orders. Based on the characteristics of China’s e-commerce live streaming platforms and users, this paper explores the impact of e-commerce live streaming on consumers’ purchase intentions under the mobile Internet environment. During e-commerce live streaming, consumers are likely to produce a herd effect, thus influencing their purchase intention. Results show that perceived ease of use, situational factors and follow others’ behavior significant impact on purchase intention, perceived usefulness of influence on purchase intention is lesser, incomplete information will not directly affect consumer’s purchase intention, but by following others it might affect their purchase attitude when watching live.