Digital Transformation and Global Society

The article analyzes the role of state information systems in building a democratic information society. The information available through such information systems is official information. Citizens trust such information, plan and base their actions on it. Meanwhile, unlike special state portals, the information systems of individual state and municipal bodies are not always distinguished by high quality of the data. Even if some information is actually present in the system, it may not be detected by a simple search query. This is misleading users. To solve this problem, technical, organizational and legal measures are needed. The authors formulate a presumption of authenticity of official information. A citizen has the right to rely on official information as a reliable one, his behavior based on such information should be regarded as conscientious. A classification of state information systems on the legal significance of the information contained in them is proposed. The authors make some proposals on the development of international legislation on guarantees of access to government information.

In public policy theory there is a problem of just procedure which could be used in obtaining a fair result in decision. Blockchain as a network of distributed registers is often positioned as an institution ensuring the fairness of decisions by voting on the basis of a consensual procedure. Consensus is achieved in the blockchain interactions through various algorithms (Proof of Work, Proof of Stake, Byzantine Fault Tolerance, Modified Federated Byzantine Agreement) that provide different rules for a procedural justice. Current political theory distinguishes between pure, perfect and imperfect procedural justice. The article analyzes the political ontology of the pure procedural justice of blockchain-technology. This ontology relies not on the legal nature of interaction in the network, but on the technical and social immediacy of trust, cooperation and co-production. The empirical basis of the study is the analysis of cases of using blockchain-voting on the platform of “Active Citizen” (Moscow).

Expert networks that are the community of professionals have become more popular in/over the last years. The paper presents a method of human community forming in expert network for joint task solving that is based on competence management approach. Related work analysis has been implemented and the requirements for the method development have been identified. The proposed method allows user to find the best possible community of experts for the reasonable time that is related to the number of experts and the number of skills in the competence management system.

‘eParticipation’ means the involvement of citizens in the political process via information and communication technologies. This paper analyses the identification of target groups in eParticipation and the elaboration of their behaviour. Research and analysis was conducted on a target population in Germany. Second and third generational citizens were the focus of the analysis. The city of Friedrichshafen was chosen due to its inherent electronic and network infrastructural advantage. It is assumed that this city’s mode of connectivity will be established in the whole country in the years to come. The research methodology was quantitative; a survey was conducted to collect statistical data. Questions for the survey were derived from literature-based research in adjacent areas. Topics in the survey include ‘eGovernment’, ‘technology-acceptance’ and ‘target group behaviour’. Survey locations were chosen close to administrative institutions, aiming to elicit responses from long-term citizens of Friedrichshafen. In total 249 people were surveyed. This represents a confidence level of 94%. Four distinctive target groups of adults were identified and categorized according to experience: “First-time Voters”, “Amateur Voters”, “Professional Voters” and “Expert Voters”. Research results showed a strong tendency of the respondents towards eParticipation provided its direct political impact was being limited. Moreover, the strongest concerns about an online election were voter-manipulation and vote-buying. Local administrations and politicians can use findings from this research to implement technologies and to encourage their target audience to participate electronically in the political discourse.

The paper presents a methodology for e-participation portals social efficiency assessment based on the United Nations (UN) approach. The system of indicators frames a political decision-making cycle and covers 3 dimensions of social efficiency such as political, technological and socio-economic. The methodology developed involves factors that are available from open sources. The authors present results of the methodology approbation on 5 e-participation portals in Russia. The findings have revealed the portals studied show the least progress in socio-economic dimension of social efficiency compared to political and technological ones.

In this paper, I introduce and discuss a new model of governance, in which epistemic qualities of intrinsically elitist open deliberation are combined with normative qualities of aggregative democracy based on universal suffrage. In our model, these two approaches, typically considered as opposite to each other, are combined in a quite natural way. Namely, the process of deliberative policy-making in a community is open to every its member who is willing to participate (the “active” ones); while all others (the “lazy” ones) are provided with the possibility of either to cast their informed vote, or, at the end, to delegate their voting right to the whole community, through an IT system enforcing appropriate procedures and performing appropriate algorithms. Practical implementation of our model will be made possible through a combined use of (1) a procedural framework for Mass common Online Deliberation (MOD), which had been described in detail in our past papers; (2) an appropriately designed Computer-Assisted Argumentation (CAA) system; and (3) a system for collecting and taking into account individual preferences of every “lazy” citizen, in a way similar to the so-called Voting Advice Application (VAA) systems.

At present, a large number of information systems have been created that operate productively and provide information support of specific functions. Currently, a topical issue is to unite these information systems, create favourable conditions for their information interaction. This task is particularly important for the creation of an information infrastructure in the electronic government, which involves both large-scale state systems and applications automating local functions. The main part of system interoperability is defined by semantics – tools for transfer of meaningful data, information. Semantics in information space is defined by two components: identification of objects and NameSpace.In different information spaces the problem of semantics provision is solved in a customized way. In semantic web, it is possible to use standard NameSpaces, or create your own one. An automatically generated URI is used as identifiers.There are alternative options to reproduce semantics in the framework of information infrastructure. In practice, there are cases where identifiers are a profound business key containing information about individual elements of business logic, the result of which is the object described. The article describes examples of such practice and shows elements of the methodology for creating such identifiers.The second semantics element is the namespace. In this field, serious groundwork has been made in different economy sectors. There is a tendency of interaction between separate dictionaries and development of uniform approaches. This can be implemented through creation of templates.Currently, the prerequisites for combination of two elements of semantics definition are fulfilled: identifiers and namespaces. This would make it possible to move quickly towards the creation of an e-government information infrastructure.

This paper discusses digital transformation in the Eurasian Economic Union and provides an analysis of possible risks. A classification of risks is proposed, existing forecasts of the development of the digital economy in Russia and the EEU are considered. The study makes account of existing economic disparities and political factors. The authors offer their scenarios of digital transformation within the EEU and the union’s transition to e-government.

As research on smart governments continues to attract interest, the concept of smartness seems to be growing in scope and complexity. This paper uses the scientometrics analysis to examine literature on smart cities and governance and situate the research conducted on this topic. Results suggest that research on smartness is interdisciplinary and, although spread across a variety of domains, it remains scant on topics such as e-participation and e-governance. The findings shed light on the importance of on-going examinations of smartness at the theoretical and conceptual levels for practical research endeavors.

The use of targeting as election technology in campaigns increases in western democracies with each electoral cycle, and every time new forms and methods are being applied. During the last presidential campaigns of B. Obama, D. Trump, and E. Macron, targeting was actively used to improve the effectiveness of the impact on the target audience of voters. The Russian school of political consulting traditionally uses new western technologies, adapting them to the nature of the political process in Russia. This article examines the pattern of usage of different targeting methods during campaigns in the State Duma elections. The research involves expert interviews with political consultants who were professionally connected to the planning and conduct of election campaigns. Internet targeting is gaining its popularity among Russian political consultants to carry out targeted work with some groups of voters in social media. The development is slower than that in Western countries due to the lack of tried-and-tested tools, high financial costs, and indifference to politics of most Russian web users. The prospects for using microtargeting in Russian political campaigns are somewhat ambiguous due to the existing legislative restrictions and, in general, the need itself for such an in-depth method of agitation.

Taking into account the global world trends in the development of digital technologies and their diffusion into the economic and social space, it is proposed to use indicators of social interest in ecological matters (environmental responsibility and environmental concerns) for the population of Russian regions. An original approach to the estimation of these indicators according to the online activity of the population was proposed. It was found out that the data on the number, prevalence and dynamics of search queries for keywords related to environmental pollution, cleanliness of water and air, reflect the degree of responsibility and concern of the population with the environmental situation in the region and can be considered as an indirect indicator of environmental ill-being. Dependencies have been established between indicators of environmental interest and environmental monitoring data.

The article discusses the problems of power asymmetry and political dynamics in the era of Big Data, assessing the impact Big Data may have on power relations and political regimes. While the issues of political ethics of the data turn are mostly discussed in relation to democracies, little attention has been given to hybrid regimes and autocracies, some of which are actively introducing Big Data policies. We argue that although the effects of Big Data on politics are ambivalent, it can become a powerful instrument of authoritarian resilience through ICT-facilitated repression, legitimation and cooptation. The ability of autocracies to become data-driven depends on their capacity, control powers and policies. We further analyze the state of the Big Data policy in Russia. Although the country may become a case of data-driven authoritarianism, it will be the result of the current discursive and political competition among actors. The ethical critique of Big Data should then be based on the empirical findings of Big Data use by non-democracies.

The paper is devoted to the analysis of collective actions in modern Russia. The author analyzes the approaches to understanding collective action in the modern socio-political process. The transformation of collective actions and the emergence of a new phenomenon - on-line collective action are analyzed in the paper. The degree of significance of on-line collective actions and the possibility of their impact on the socio-political situation is analyzed.The paper includes the survey of experts from 21 regions of Russia in 2014, 14 regions in 2015, 16 regions in 2017 with a limited 10–16 number of experts for each region. The author analyzes the regional features of the organization of collective actions. The study is made possible to reveal the gradual growth of the importance and influence of the Internet of forms of collective action. However, the forms still have much less influence than traditional forms of collective action.The paper identifies the features of online collective action in comparison with off-line collective actions. The author reveals the peculiarities of the reaction of the authorities to collective actions, revealing the features of the reaction to online collective actions. The author identifies the features of organizing collective actions both in off-line and on-line spheres.

At present, the use of artificial intelligence technologies (AI) have become a general trend even in the areas normally appertained by humans. Smart technologies are actually widely used to ensure functioning of many vital sectors of economy such as public transport, communications, nuclear energy, space, medicine, etc. Such tendency also evokes the question about the use of AI for public administration and not only from the point of view of technology or ethics but also from the legal point of view. In this article, the authors seek to suggest a number of ideas and assumptions about general and specific legal issues on the use of AI for public sector, such as legal status and responsibility of AI, public trust and influence on Human rights.

Internet regulation in Russia has vigorously expanded in recent years to transform the relatively free communication environment of the 2000s into a heavily regulated one. Our goal was to identify the topic structure of Russian media discourse on Internet regulation and compare it between political and non-political media outlets. We used structural topic modeling on 7,240 texts related to Internet regulation that appeared in the Russian media in 2009–2017. We discovered the non-linear dynamics and the larger share of political media covering Internet regulation over years and compared the topics specific to political and non-political media outlets. We found out that most topics had a different share between political and non-political media and that discourse on law belongs largely to the political media. We also identified four clusters in the topics of media coverage of Internet regulation in Russia related to the law, norms, politics, and business, and the time references of particular topics. In addition, we show the parallel dynamics of the topics on site blockings and political opposition and provide the background on legislation and public opinion on Internet regulation in Russia. Our results demonstrate a rather politicized nature of Internet regulation and its connection to a broader political context in Russia.

The paper compares information security policies of two countries, Russia and Armenia. Provided the common historical past, two countries have a close cultural, historical and, partially, language basis. Moreover currently both countries tightly cooperate, particularly, in political, economic, and military fields. As cases for comparison, we choose countries – members to such international regional organizations, as Eurasian Economic Union (EEU) and Collective Security Treaty Organization (CSTO). In accordance with the Index of Democracy, Armenia and Russia are countries in democratic transition. However they have different approaches to information security – more liberal in case of Armenia and more centralized in case of Russia. We use two levels (legal and practical) to analyze cyber strategies, institutions and experience (policies) of two countries. First of all, we provide deep and comprehensive literature review on information security. The latter is performed on the following aspects of international information security: theoretical, legal, activities of international organizations, as well as Russia and Armenia positions on these issues. Second, we analyze key theoretical concepts (information security, information warfare, etc.) and approaches to them in academic and political communities. Third, we reveal basic doctrines and policy papers regulating information security policy in these states. One of the ways to evaluate information policy effectiveness is based on comparison of countries’ positions in global rankings (e.g. ITU Global Cybersecurity Index). In addition the research considers official statistics data, experts’ surveys, public opinion polls and media publications.

The article is devoted to the analysis of results of levels of information-legal culture of modern youth. The research has been conducted among young Moscow residents during 2017 and is devoted to the issue of development of legal culture of school children and copyright compliance in respect of intellectual property items.The survey was conducted by questioning. The questions were drawn up on the basis of expert polls of specialists in the sphere of copyright protection. The results of social research allowed to estimate the level of information-legal culture of youth in terms of copyright compliance for intellectual property.Also the article suggests the ways of advancement of level of information-legal culture of pupils on the basis of development of upbringing and education methods, particularly within specialized training courses for secondary school.For the courses the learning content is worked out, the ways of evaluation of level of information and legal culture of pupils are selected, the main methodical principals while executing the courses are formulated, and also the requirements for the level of grasping of learning content are set.

The paper substantiates the possibility of the Russian Post’s participation in the Smart City projects due to the integration of a smart city’s information systems and the postal services’ assets for the collection of the urban data and support of the information processes inherent in the city economy in the information society stage. Integration will improve the results of a smart city’s management and the provision of municipal services to citizens through the use of the technologies underlying the digital economy by the postal services. The transition of the postal authorities from the different countries and the Russian Post to the provision of digital services determines their willingness to become full participants in the Smart City projects launched around the world. The authors present the results of an analysis of international sources and an online survey of the Russian citizens in order to justify the relevance of the research, identify the opinions of the citizens to the Smart City projects, the participation of the Russian Post in the similar projects. The survey reveals the respondents’ attitude to the use of the digital technologies, IoT in the city initiatives, assessment of the potential of the Russian Post in implementing the Smart City projects.

The paper contributes to literature on smart cities by focusing on the demand side of smart city projects. For this endeavor, the SCOT approach is used to describe the construction of the concept of Smart City from the perspective of the mass media agenda and, in particular, from citizens’ needs and expectations in the city of Saint Petersburg, in Russia. Authors used an automated tool to perform content analysis on 589 articles that discuss smart cities in the Russian media from 2010 to 2017 as well as a survey of 421 citizens in the city. Findings suggest that the prevalence of technical descriptions involving the Smart City topic do not reduce citizens’ interest in the phenomenon nor foster their willingness to participate in city management through ICT.

Smart cities can be regarded as the latest administrative reform and digital innovation in most metropolitan cities globally. In smart cities as well as in former urban New Public Management modernization and Post Weberian reforms, the important role of the citizens in planning as well as monitoring has been highlighted. Online and offline participation along with feedback can reinvigorate town planning and policymaking as well as policy monitoring processes at the local level. The UK as many other countries reacted to this trend by offering new channels for online participation. The new participative innovations allowed for more participation and more influence by citizen. FixMyStreet is a crowdsourced monitoring instrument implemented in the UK. How it works, what the role of the state and civil society represent, and is crowd monitoring vote-centric or talk-centric will be discussed in the paper. It represents a successful bottom-up innovation approach that was used by numerous municipalities. It is a successful public private partnership and a mix between ‘invented’ and ‘invited’ space, where the role of the state is redefined.

The population mobility, related to long-term and short-term migrations, happens on an increasing pace, affecting various fields of activity in a single country and the world community as a whole. Large amounts of diverse migration-related data are recorded by different entities all over the world, making it important to develop and implement a system for storing and analyzing such data. The proposed article describes the subject area associated with socio-economic displacements of people, the key features of internal and external migrations are noted. Based on that, the general architecture of the universal system of data storage and processing is proposed leveraging the client-server architecture. A fragment of the data model, associated with the accumulation of data from external sources, is provided. General approaches for algorithms and data structure usage are proposed. The system architecture is scalable, both vertically and horizontally. The proposed system organizes the process of searching for data and filling the database from third-party sources. A module for collecting and converting information from third-party Internet sources and sending them to the database is developed. The features of the client application, providing a convenient visual interface for analyzing data in the form of diagrams, graphs, maps, etc. are specified. The system is intended to instrument various users interested in analyzing economic and social transfers, for example, touristic sector organizations wishing to obtain statistics for a certain timeframe, airlines planning flight logistics, as well as for state authorities analyzing the migration flows to develop appropriate regulations.

The digitalization of public administration presents significant challenge for many municipalities. At the same time, many larger cities have well progressed towards applying Information and Communication Technologies (ICT) to develop modern urban spaces, commonly referred to as Smart Cities. Smart Cities are complex systems whereby ICT plays an essential role to address the needs of many stakeholders. Obviously public services are key for the development. However many municipalities and cities face challenges to transform and digitalize these services. Although single projects are often successful, the coordination and coherence of services, the consideration of many stakeholders together with strategic alignment is complex. The concept of Enterprise Architectures is seen in many organizations suitable to manage the complexity of heterogeneous systems and technologies. Therefore in this paper we extend our earlier work, and present key concepts for Enterprise Architecture Management in Smart Cities that can assist cities and municipalities to digitalize and transform public services. We particular focus on the alignment and connection related to the service layer in the Architectural Framework, and present key concepts related to this layer.

Traffic analysis using computer vision methods becoming an important field in the traffic analysis research area. Despite this, common traffic models still rely on traffic planning methods, which treat all cars uniformly, meanwhile special vehicle can bypass traffic rules. Considering this, special vehicle can travel noticeably faster by avoiding traffic jams. This paper presents an analysis of special transport behavior case - movement by the opposite lane(MBOL). Our goal is to analyze under which conditions, such kind of specific traffic behavior happens and to present a regression model, which further can be used in special transport route planning systems or transport model simulations. The video from the traffic surveillance camera on the Nevsky Prospect (the central street of the city of Saint-Petersburg) have been used. To analyze traffic conditions (and detect MBOL-cases) we use well-established computer vision methods - Viola-Jones for vehicle detection and MedianFlow/KCF for vehicle tracking. Results show that MBOL happens under extreme main lane conditions (high traffic density and flow), with wide variety of parameters for the opposite lane.

Modern solutions based on machine learning and map data are discussed in the paper. A convolutional neural network is proposed to use for urban spaces tree canopy evaluation. The developed method allowed to formulate a criterion for assessing the “green” infrastructure of a territory. The index, called Abin, is proposed to be used to estimate the area of woody plants. The process of preparing training datasets and carrying out search studies on the model of the neural network used are described. The results of training and testing of trained networks in arbitrary areas of the city are given. The analysis of the final results is carried out for the training errors revealed in the test cases, the prospects for the application of the trained models, the proposed method for estimating the “green” environmental conditions by the Abin index.

The review discusses the political-economic aspects of the concept of distributed capitalism allowed for by blockchain technology. As opposed to the first era of the Internet, where the industry of financial and information services was dominated by intermediaries, the blockchain era is characterized by development of a new institution of trust; disruption of financial intermediation; economic inclusion of hundreds of millions of citizens in developing countries; an increase in competition and a decrease in inequality. The paper focuses on the content of key political-economic categories being redefined in the blockchain era. First, labor value gives way to creative value which is manifesting itself in cryptocurrencies. Second, exploitation of workers is replaced by digital discrimination. The blockchain revolution is a solution to the problem of discrimination against intellectual property creators, who have to hand over a large part of the value created to intermediaries. Third, capitalism characterized by information monopoly gives place to free competition based on rivalry between cryptocurrencies. Fourth, class struggle is substituted by confrontation between agents of information monopoly system and those of distributed economy. The author considers the main opposition to distributed capitalism to stem from the feudal financial system which loses ground under new conditions, where economic agents may use alternative currencies and interact directly with one other without risk and high transaction costs.

In recent years more and more participants of the retail segment of the banking sector of Russia are launching platform-based value chains along with traditional linear value chains. As a result, business organizations are transforming into a complex system within which customers, banks and retail chains enter into business relations with each other as well as the platform itself, the owner of which is one of the participants of this interaction. A new kind of value exchange is the result of this which has become possible due to the existence of the platform. Platforms complement and compete with linear value chains in order to attract customers. In this article a comparison of these two types of value chains is presented using the example of purchasing goods by installments in Russia, their peculiar workings are also distinguished.

This paper is about evaluating product competitiveness in the IT market. The developed model is explained on the integrated approach that takes into account the dynamics of competitive positions and market structure. It reveals the changes of structural features in the IT market based on the index of structural shifts. The dynamics of competitive positions are proposed to be evaluated with the vector model. The procedure consists of two stages. Firstly, competitive position is estimated by means of expectancy-value model. Secondly, the index of product profitability is evaluated. Finally, we can form a vector of competitive position based on these two indicators and model the dynamics of it. Thus the comprehensive model of product’s competitiveness is offered and managerial implications to develop the IT products’ competitiveness are provided.

It has been said “all design is redesign”, and it is particularly true for websites, whose number in the today’s online environment has reached 1 billion. In our paper, we justify case-based approach (CBR) to designing web user interfaces (WUIs) and outline some currently unsolved problems with its application. In this research work, we focus on definition and measurement of similarity, which is essential for all the stages of the CBR process: Retrieve, Reuse, Revise, and Retain. We specify the structure of a case in the web design domain (corresponding to a web project) and outline the ways to measure similarity based on the feature values. Further, we construct artificial neural network model to predict target users’ subjective similarity assessments of websites that relies on website metrics collected by our dedicated “human-computer vision” software. To train the model, we also ran experimental survey with 127 participants evaluating 21 university websites. The analysis of the factors’ importance suggests that frequency-based entropy measure and the proposed index of difficulty for visual perception affected subjective similarity the most. We believe the described approach can facilitate design reuse on the web, contributing to efficient development of more usable websites crucial for the e-society advancement.

Supply chain management is struggling with a bunch of issues that appear during supply chain members coordination. Raising of supply chain complexity leads to the necessity of developing new software applications, which can be used for analysis of supply chain dynamics, storing data about it’s past and present states, predicting future behavior. This paper discusses current challenges in supply chain management and presents a model for the multi-agent framework in order to investigate supply chain dynamics.

The progress in IT gave people a bigger space for fraudulent activity. To help the analysis of criminal financial activity special software was invented. The problem is that the machine of money laundering becomes more sophisticated, but present ways of detecting such activities cannot match the level of fraud capabilities. The main objective in this case is finding methods to improve the available systems and designing new algorithms, understanding all principles that are used in money laundering. To accomplish this, all the steps in AML-systems should be revised or developed from the beginning, new tools should be included. This article gives an overview of the current situation with analysis of weaknesses in present AML-system versions and shows the examples of using machine learning.

Increasing studies on sharing economy address a fast growing and spreading across the world phenomenon. Massive distribution of sharing economy applications contributes to co-evolution of consumer perceptions of the advantages, risks and opportunities of collaborative consumption. Future dynamics and transformation of sharing economy depends on both supply and demand sides of its diffusion as a digital business model. By diversifying the same concept (e.g. UBER) across the countries and contexts providers adapt to business environment, including existing regulation, protective measures, consumer perceptions and expectations. The current study is based on a large-scale survey of Russian consumers, evaluating their experience and expectations in the area of sharing economy in a context of an emerging market. As emerging markets face numerous market inefficiencies, they might be the most active and willing adepts of sharing economy practices. This adoption however is determined by the readiness and ability of both businesses and consumers in emerging market to deploy the full potential of collaborative consumption. Moreover, other determinants might be the differences in sharing economy consumer behavior, expectations and norms in emerging markets.

This paper addresses the issue of creating the methodology that could help to answer the question about assessing the effects of a given export policy. The new approach for constructing and calculating the import countries ranking is proposed. The peculiarity of such problems lies in the weakly formalised set of factors that define the import rank of every country. The question is also complicated by the excessive flow of information which may be unreliable and contradictory. Therefore, the possibilities of statistical methods to support the solution of such a problem are limited. To forecast and support export solutions for the short and medium term, the concept of “Rank of the country’s import priority” (Priority Index, PI) is introduced. It is built on historical data with applying the econometric methods. For the medium and long-term perspective and for taking into account non-quantitative factors, it is suggested using the methods of networked expertise (e-expertise), cognitive modelling, artificial intelligence (AI), inverse problems solving on cognitive model with genetic algorithms, and Deep Learning.

We apply social network analysis to examine school choice in the second-largest Russian city Saint-Petersburg. We use online data (“digital footprints”) of between-schools comparisons on a large school information resource shkola-spb.ru . This resource allows to identify clusters of city schools that have been compared to each other more often and thus reflect choice preferences of students and parents looking for a school. Network analysis is conducted in R (‘igraph’ package). For community detection, we employed fast-greedy clustering algorithm (Good et al. 2010). The resulting communities (school clusters) have been placed on a city map to identify territorial patterns formed according to choice preferences.Network analysis of the district school networks based on between-schools online comparisons reveals two main factors for community formation. The first factor is territorial proximity: users compare schools that are relatively close to each other and not separated by wide streets, parks, industrial areas, rivers, etc. The second grouping principle is the type of school: private schools always form a separate cluster which shows that they are not being compared with public schools. In one district there was also a cluster of elite or academically challenging public schools grouped together.

The main focus of this paper is the analysis of universities’ embeddedness into industrial sector of the Russian Northwestern region. We use webometric approach to evaluate the collaboration of universities with the use of Social Networks Analysis, as well as the examination of co-authorship network among universities and other agents. We develop our research within the framework of Triple Helix concept, taking only two agents from there: universities and companies. As a result, we found two groups of universities: which have a lot of connections with a variety of industrial and business companies and behave as key agents for the whole network as well as some with more narrowly focused types of collaboration, having fewer links with companies.

One of the research directions of Internet public data is the social profiling task. Various analytical tools and technologies are used to quickly process large arrays of heterogeneous data within this task. The result is a social profile or a set of profiles. It represents value in various socio-economic spheres.This article offers practical examples of social profiles application in various socio-economic tasks. A survey of existing works on social profiling task has been reviewed. There are suggestions of using social profiles built by Big Data technologies in the future of Russia and the world.This work is carried out with the support of RFBR grant №18-07-00408 in a research project named “Fundamental theoretical bases development for self-adaptation of applied software systems”.

Fake news (fake-news) existed long before the advent of the Internet and spread rather quickly via all possible means of communication as it is an effective tool for influencing public opinion. Currently, there are many definitions of fake news, but the professional community cannot fully agree on a single definition, which creates a big problem for its detection. Many large IT companies, such as Google and Facebook, are developing their own algorithms to protect the public from the falsification of information. At the same time, the lack of a common understanding regarding the essence of fake news makes the solution to this issue ideologically impossible. Consequently, experts and digital humanists specializing in different fields must study this problem intensively. This research analyzes the mechanisms for publishing and distributing fake-news according to the classification, structure and algorithm of the construction. Conclusions are then made on the methods for identifying this type of news in social media using systems with elements of artificial intelligence and machine learning.

During the disaster periods, a large amount of information is created and distributed online through news media sites and other Web 2.0 tools including Twitter, discussion boards, online community, and blogs. As scholars actively debate on information dissemination patterns during the disasters, this study examined how individuals utilized the different forms of the Internet in order to generate relevant information. Using a big-data analysis of 3,578,877 online documents collected during 50 days periods each about the Gyeongju earthquake, and MERS, our results found that 1. The amount of information and its distribution by online platforms is significantly different between two disaster cases, 2. The proportion of daily generated documents during the disaster periods showed different patterns during each disaster case, 3. While the amount of daily generated information was gradually decreasing during the Gyeongju earthquake case, the information collected from non-media sites was increasing during the MERS period. The results highlight that individuals may utilize the Internet differently to deal with disaster-related information based on type of disaster. Therefore, a simple model would not accurately predict the online information dissemination pattern during the disaster.

In this work, we analyse the structure of local and regional market of player transfers in popular eSports discipline Dota 2. Together with team performance metrics, these data provide us with an opportunity to model network of transfers between teams. In turn, the transfers show the actual structure of mobility in the industry. We collected the data on players’ transfers for the top professional teams and their transfer partners, based on transactions between two world tournaments: The International 16 to The International 17. We built a directed network of transfers and analysed centralities, assortative mixing, and link formation.The global transfer market structure is organised around continental regions. At the same time, teams with the same level of performance rarely have transfers. This can be a reliable indicator of the presence of mobility lifts, in this case, mastodons of the tournament accept in their ranks natives of the less rated teams. On the other hand, some successful players may leave the best teams to establish their own, in the same way as top managers leave the large corporations to launch startups.

The research outlines major self-presentation strategies and gender patterns of the online dating application Tinder users in Moscow. Authors conducted the case study and analysed 400 profiles of 20–40 years old female and male app users. Upon the content analysis, few patterns of gendered self-presentation were depicted, explained further through the prism of gender roles theory with the focus on the dominant cultural traits in modern Russia.

Virtual communities of practice are becoming more and more efficient for professional knowledge sharing. Thus, most active internet platforms where professionals exchange their experience could be considered as the representation of current professional knowledge state. In this work in progress we analyse the structure of professional knowledge in IT sphere through the investigation of Stack Overflow. An analysis of bipartite network which connects question tags and IDs of users with the help of overlapping community detection algorithm allows to identify the intersections of different skill areas. Meaning the user reputation, we examine whether having the competencies in several areas at the same time (e.g., several programming languages) is more profitable for professionals than specific skills in the narrow field or not. The long-term goal of our study is to develop a metrics for the evaluation of user’s professional expertise and professional knowledge complexity based on the skills overlap.

In this paper, the problem of fake accounts in online social networks is addressed through the lens of resulting misstatements of the structure of network interactions between users. The study of a network as a social space becomes difficult because of additional noise created by fakes. The aim of the present paper is to assess the impact of fake accounts on the characteristics of local friendship networks between users of VKontakte website in Izhevsk (Russia). The authors highlight key characteristics recognizing a fake account and present experience of the design of classifier (based on random forest algorithm) to determine the authenticity of an account. Comparison of the VKontakte network topology before and after removing the fake accounts from it shows what specific network metrics are affected by the presence of fake profiles. It was found that as the fakes are being excluded the less integrated members lose contact with most part of the network while the number of its components increases. “Fakes” serve as strong link concentrators distributed throughout the network and these fakes overestimate observed levels of assortativity and transitivity.

Social networks are important part of society. Analysis of information flows and activity of users may provide different opportunities for scientist. However, existing methods and models for prediction of information flow couldn’t provide sufficient level of accuracy. Proposed method of information flow analysis is based on machine learning algorithms. First stage of research aims to analyze the features, that could be useful for describing activity of users and information in social networks. Data was assembled from social network “VKontakte”. Data includes main information about selected features for each person. On the second stage were conducted experiments, based on machine learning methods. Three main approaches were implemented in research - naive Bayes classifier, logistic regression analysis and k-means clustering. A comparison of different machine learning methods was conducted on last stage. Best results of predictions were reached by usage of naive Bayes classifier. Proposed method for prediction of information flow is usable for organizing users’ protection from different type of information attacks.

The healthcare sector generates large amounts of data on a daily basis. This data holds valuable knowledge that, beyond supporting a wide range of medical and healthcare functions such as clinical decision support, can be used for improving profits and cutting down on wasted overhead. The evaluation and analysis of stored clinical data may lead to the discovery of trends and patterns that can significantly enhance overall understanding of disease progression and clinical management. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a data mining project approach to predict the hospitalization period of cardiovascular accident patients. This provides an effective tool for the hospital cost containment and management efficiency. The data used for this project contains information about patients hospitalized in Cardiovascular Accident’s unit in 2016 for having suffered a stroke. The Weka software was used as the machine learning toolkit.

In 2014–2015 years the very first sociological study of Russian crunchers [20] – volunteers who provide their computing resources for solving laborious tasks was conducted by authors. The study covered almost 650 people, which is a representative sample (more than 16% of total sample of about 4000 crunchers). A detailed analysis of that survey data led the authors to the idea of developing a new approach to evaluation of VDC projects. It is based on expert assessments of project quality on many criteria such as clarity of concept and vision, sound scientific platform, as well as existence of visualized results, availability of tools for encouraging crunchers, and so on. A new tool for assessing the quality of VDC projects (the YaK-index) is proposed and described in this paper. It was applied for evaluating some VDC projects to identify their strong and weak features, to make recommendations for improving their efficiency, to enhance the attractiveness for those interested in the VDC, and to create conditions for providing comparable information to the leadership of VDC projects. This paper describes the YaK-index idea and methodology, some stages of its development. Examples of visualization of comparable results of evaluating for a number of projects are given.