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2022 | Book

Digital Transformation and Global Society

6th International Conference, DTGS 2021, St. Petersburg, Russia, June 23–25, 2021, Revised Selected Papers

Editors: Daniel A. Alexandrov, Alexander V. Boukhanovsky, Andrei V. Chugunov, Yury Kabanov, Olessia Koltsova, Ilya Musabirov, Sergei Pashakhin

Publisher: Springer International Publishing

Book Series: Communications in Computer and Information Science


About this book

This volume constitutes refereed proceedings of the 6th International Conference on Digital Transformation and Global Society, DTGS 2021, held as a virtual event in June 2021. Due to the COVID-19 pandemic the conference was held online.

The 34 revised full papers and 4 short papers presented in the volume were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on ​eSociety: social informatics and digital inclusion issues; ePolity: e-governance and regulation; eCity: smart cities and urban planning; eHumanities: digital education and research methods; eCommunication: online discources and attitudes; eEconomy: challenges of the COVID-19 pandemic; eEconomy: e-commerce research.

Table of Contents


eSociety: Social Informatics and Digital Inclusion Issues

What is Fake News? Perceptions, Definitions and Concerns by Gender and Political Orientation Among Israelis

“Fake news” is a growing concern among scholars, policymakers and the public. The phenomenon has gained much scholarly attention in recent years, however, most research has been occupied with its manifestation in the United States. To complement on the global nature of the phenomenon, the study evaluates how Israelis perceive its sources and the responsibility of various institutions. The analysis compares trends related to gender gaps and political bias in fake news perception to studies from the US and Europe. Findings illustrate how political orientation correlates with perception of fake news and the main source of false information in the media landscape, such that conservatives associate fake news mostly with mainstream media and journalists, whereas liberals associate politicians and social network users with fake news. Additionally, men and women differ in perceptions, subjective experience of fake news and concerns over the implications of the phenomenon. These trends and their comparison to US and European research contribute to a more complete understanding of fake news as a universal phenomenon.

Nili Steinfeld
A Semi-automated Pipeline for Mapping the Shifts and Continuities in Media Discourse

Mass media are an important actor between the authorities and citizens. Mass media frame the news and set the agenda for public debates. Investigation of this role of media has inspired various techniques for the analysis of media discourse in social and political research. However, manual coding of large corpora takes a long time and is prone to bias. Topic modeling can automate the search for key terms but it can hardly trace the shifts in a debate if the key terms are changing over time. In this paper, we propose a clustering-based pipeline that automates the search of key terms in the media discourse on a given topic and traces their development in time. The proposed technique helps to connect the clusters of unique terms across time periods into ‘discursive streams’. Such streams’ relative proportions and contents can be compared on a resulting map, a river network. The steps for creating such maps are explained. Two use cases demonstrate the shifts and continuities in the national media discourse about Internet regulation and labor migration in Russia over almost a decade. The analyses are based on more than 5,000 texts coming from the Integrum and media archives. The resulting networks show which discussions evolved in the media discourse in the media coverage of these topics; how the key terms changed over time within the same debates; how the discursive streams grew in size and died out. The results are discussed in terms of validity and the applicability of the proposed technique to the study of media coverage of other topics.

Anna Shirokanova, Olga Silyutina
Average Nearest Neighbor Degree and Its Distribution in Social Networks

The paper is focused on the analysis of average nearest neighbor degree (ANND) in complex social networks. The ANND of nodes with degree k is defined as the average degree of their neighbors over all nodes with degree k. ANND is one of the well-established tools for the analysis of degree-degree correlation and assortativity in complex networks. In this paper, we analytically examine the properties of ANND in undirected networks generated by the Barabási-Albert model. First, we prove that for every node, the average degree of its neighbors is increasing logarithmically over time. Then we show that the ANND distribution at each iteration is uniform, i.e. the values of ANND are the same for every k, and therefore, Barabási-Albert networks are uncorrelated. Moreover, we compare the ANND distributions in simulated graphs (derived by the Barabási-Albert model) with distributions in real-world social networks (Twitter, Facebook, GitHub and Flickr).

Alexey Grigoriev, Sergei Sidorov, Sergei Mironov, Igor Malinskii
Offline and Online Civic Activity: General and Special

The article is devoted to the analysis of offline (traditional activity) and online (Internet activity) activity in modern Russia. The article presents the results of a study of civic activity in Russia, which has been conducted by the method of experts` survey (hold on since 2014).The article focuses on the analysis of differences and similarities of online and offline civic activity. The assessment of the level of development of online and offline civic activity is given. At the moment, there is an uneven development of offline and online activity in the socio-political sphere in Russia. Experts’ estimates indicate the superiority of online activity over off-line in terms of popularity and demand. At the same time, the state reacted almost equally to the manifestations of offline and online civic activity. The reasons for the popularity of the Internet, the level of its influence on the socio-political reality are indicated. The analysis of the formation of associations in offline and online coalitions of NGO and civic activists is carried out. The state's attitude to the manifestations of offline and online civic activity is determined.The results of the study suggest that both real and virtual spaces for the implementation of civic activity are interconnected and unified in nature. Online and offline civic activity do not have clear and serious differences in their manifestations. The spaces themselves have their own specific features of functioning. However, collective actions on the web and in the real world are carried out to implement different forms of civic activity and using the same mechanisms to achieve goals.

Alexander Sokolov, Asya Palagicheva, Alexander Frolov
Recognition of Signs and Movement Epentheses in Russian Sign Language

Automated translation from sign languages used by the hearing-impaired people worldwide is an important but so far unresolved task ensuring universal communication in the society. In our paper we propose an original approach towards recognition of Russian Sign Language (RSL) based on extraction of components: handshape and palm orientation, location, path and local movement, as well as non-manual component. We detail the development of the dataset for subsequent training of the artificial neural network (ANN) that we construct for the recognition. We further consider two approaches towards continuous sign language recognition, which are based on sequential search of candidate events for the next sign start and the complete identification of the speech elements – the actual signs, resting state of the signer, combinatorial changes in the parameters of the signs and the epentheses.

Mikhail Grif, Alexey Prikhodko, Maxim Bakaev
Digital Inclusion Through Sustainable Web Accessibility

In the age of digitalization, the business environment is changing dynamically due to the growing consumers’ demands of the products and services provided. In an effort to respond to rapidly changing market requirements, companies restrict access to their products of certain user groups with special needs due to neglecting of imposed international accessibility standards. This can even lead to disruption of the communication equipment of people with disabilities in the digital environment, which is often the only possible one. The Web remains the largest source of information used by people around the world today. Communication on the Internet is the most common. That is why achieving web accessibility is not an end in itself, but a necessity for digital inclusion of people with special needs. In this regard, the aim of the article is to propose a web accessibility audit approach that follows a well-defined sequence of stages and applies automated tools to study the accessibility issues. The approach has been tested by auditing the accessibility of educational institutions’ websites in Russia and Bulgaria.

Radka Nacheva
Lövheim Cube-Backed Emotion Analysis: From Classification to Regression

Nowadays sentiment and emotion analyses are widespread methodologies. However, most of all related tasks in classification manner use discrete classes as target variables: Positive vs Negative (sometimes accompanied by Neutral class), or discrete emotion classes (as Anger, Joy, Fear, etc.). Nonetheless, it is more likely that emotion is not discrete. In this paper, we argue that regression is more natural way to evaluate and predict emotions in text and apply regression framework in study of using Lövheim Cube emotional model for emotion analysis. A regression approach for predicting a point in 3-d space or a configuration of its diagonals can provide us with detailed analytics from an emotional diversity perspective. The preliminary results on regression values prediction performed by five different models demonstrate the need of optimization in regard to a precision. The additional conclusion is that the accuracy of classification is not affected significantly by the target variable type.

Anastasia Kolmogorova, Alexander Kalinin, Alina Malikova
Anti-vaccination Movement on VK: Information Exchange and Public Concern

Vaccination is a simple but effective way to control the spread of communicable diseases. However, an increasing number of people express their distrust in the immunization process and refuse to vaccinate themselves and their children. One explanation suggests that doubtfulness is maintained through widespread misinformation available on social media. This research takes an exploratory approach to the anti-vaccination communities in the Russian social network – VK. It applies network analysis to identify patterns in the dissemination of information and text mining to capture general public concern shown through the language of the posts published. In total, the digital fields of 135 open communities were analyzed. Textual data, public information about communities as well as reposts were collected using API technology. The results showed that the network of the communities can be characterized by a hierarchical structure, meaning that big and active communities control the information exchange within the network. At the same time, the public concern on the vaccination is associated with vaccine complications, parental worries, and uncertainty on the effects on the body.

Igor Petrov
Transformer Models for Question Answering on Autism Spectrum Disorder QA Dataset

Question answering (QA) Transformer-based models might become efficient in inclusive education. For example, one can test and tune such models with small closed-domain datasets before the implementation of a new system in an inclusive organization. However, studies in the sociomedical domain show that such models can be unpredictable. They can mislead a user or evoke aversive emotional states. The paper addresses the problem of investigating safety-first QA models that would generate user-friendly outputs. The study aims to analyze the performance of SOTA Transformer-based QA models on a custom dataset collected by the author of the paper. The dataset contains 1 134 question-answer pairs about autism spectrum disorders (ASD) in Russian. The study presents the validation and evaluation of extractive and generative QA models. The author used transfer learning techniques to investigate domain-specific QA properties and suggest solutions that might provide higher QA efficiency in the inclusion. The study shows that although generative QA models can misrepresent facts and generate false tokens, they might bring diversity in the system outputs and make the automated QA more user-friendly for younger people. Although extractive QA is more reliable, according to the metric scores presented in this study, such models might be less efficient than generative ones. The principal conclusion of the study is that a combination of generative and extractive approaches might lead to higher efficiency in building QA systems for inclusion. However, the performance of such combined systems in the inclusion is yet to be investigated.

Victoria Firsanova

ePolity: E-Governance and Regulation

What Drives Adoption of E-Services in Russia?

The expectations from digital government transformation are remarkably high, especially in public service delivery. However, the recent research points to the fact that often such impacts are overestimated, and the actual results of public administration digitalization are more modest than expected. One of the reasons for that is insufficient adoption of digital public service delivery channels especially in the countries like Russia where digital by default principle has not been established. The significant variance in regional development makes Russia an interesting case for research and comparison both for developed and developing nations.This paper aims at identifying the factors influencing citizen adoption of digital public service delivery channels in Russian regions. Based on the review of theoretical and empirical literature, we selected 11 possible factors that could be related to the extent of adoption of electronic public services at the regional level. While statistically significant correlation was found with most variables considered, no such interrelation was confirmed for age and information security risks indicators. The results of regression analysis suggest that quality of public service supply in electronic form, education, and per capita income determine the extent of digital public services adoption.Our findings demonstrate that social aspects of digital divide are more important than variations in ICT infrastructure development and should be accounted for in the ongoing and future government digital transformation initiatives.

Elena Dobrolyubova, Alexandra Starostina
Institutional Factors for Building Trust in Information Technologies: Case-Study of Saint Petersburg

The paper is devoted to finding the factors that influence on citizen’ trust in information technologies. Research has been proposed to identify which institutional factors affect the establishment of trust in information technology. Saint Petersburg was selected as a research case. The survey applied SCOT approach in assessment citizens’ use and attitudes towards new technologies. The study was conducted in two phases: pilot and main survey. In the second phase of the study, 800 respondents took part in the survey. According to the data of conducted surveys, factor analysis was carried out. The study shows that institutional trust reflected in attitudes towards organizations on the Internet is important for building trust in information technologies. People who are more inclined to trust government institutions are also more inclined to trust interactions in the Internet space.

Evgenii Vidiasov, Lyudmila Vidiasova, Iaroslava Tensina
Main Regulatory Plans in European Union’s New Digital Regulation Package

It seems clear that the Internet, as highlighted by the European Court of Human Rights in Cengiz and Others v. Turkey, “has now become the primary means by which individuals exercise their freedom to receive and impart information and ideas”. As a result, in many countries worldwide, regulating the Internet has become one of the top priorities on the political agenda, albeit with different solutions, from Australia through Germany and Canada to Poland and Hungary. The world has become acquainted with ‘fake news’, ‘deepfake’, ‘dis- and misinformation’ in recent years. Digital platforms providing services worldwide have so far not devoted significant resources – for the sake of their well-conceived business interest – to prevent these from spreading. Two proposals are on the table since December 2020 in the European Union: Digital Services Act and Digital Markets Act. Both want to set an exemplary approach to regulating tech companies and have several advantages and disadvantages. The article intends to show them all in an explanatory manner.

Kristina Cendic, Gergely Gosztonyi
Lex Informatica: Information Technology as a Legal Tool

In the era of the fourth technological revolution, the implementation of social relations depends on information technology and software systems. The program code that controls the operation of these systems begins to play the role of a regulator of social relations, since it de facto sets the boundaries of capabilities and imposes requirements on user behavior.The paper opened a discussion about what conditions are important for the program code to receive scientific recognition as a source of law. Three features are proposed to be considered necessary conditions. First, the program code must have an impact on social relations. Secondly, he must establish special rules for the participants in these relations, which are absent in legal acts, moreover, these rules de facto receive the status of mandatory if the information system (computer program, other tool) is the only way to exercise certain rights and/or responsibilities of the subject. Finally, users and other actors should accept these rules as a given, and consider opposition to them as an undesirable exception.A separate and very important issue is the attitude of the state - it must at least recognize and support the rules laid down in the code as the natural order of things in the corresponding social relations (if the state takes on the role of guarantor of such rules, for example, obliging the subjects of the right to use certain software, then the program code de facto begins to play the role of a source of law).

Roman Amelin, Sergey Channov, Eduard Lipatov

eCity: Smart Cities and Urban Planning

Detection the Relevance of Urban Functions for Value-Based Smart City Management

The article deals with the issue of value-based city management. Value-based management is one of the most important attributes of the concept of smart cities of the new generation. It relates to the transition from the technological understanding of a smart city to the concept of a city adapted to a person to create a new quality of life and create new opportunities for development. At the same time, the most important problem of implementing a value-based approach is the difficulty in quickly identifying the values and needs of citizens. Traditional methods based on sociological research do not provide the necessary speed and coverage, in addition, their results require additional adaptation for management tasks. This requires the development of new approaches to determining the significance of urban functions for citizens based on data that has operational specifics. One of the sources of such data can be social networks on the Internet. The article suggests an approach to clarifying the structure of values and needs of citizens based on the analysis of social network data.

Olga Tikhonova, Ilya Yakimuk, Sergey A. Mityagin
Identifying Troubles and Expectations of the Citizens Towards Their Habitat Based on PPGIS Approach

Citizens’ participation in evaluating the quality of the urban environment has recently gained momentum in urban planning practice. One of the promising approaches to address this task is the participatory mapping approach and one of the most established tools - public participation geoinformation systems (PPGIS). Based on the data coming from the study on the historic local area in St. Petersburg the paper shows the indicators to grasp citizens’ subjective perception of the habitat, their troubles, and their expectations. The results session presents the mapping of the items of the habitat which have subjective value - everyday places and routes, favorite and disliked places, places to change and to preserve, spatial analysis of their distribution and its objective environmental characteristics, and correlation analysis of their colocation against each other. Besides the analysis of the typology of the citizens’ expressed expectations towards the changes in their habitat is considered and interpreted. The conclusions section sums up the methodological advantages of exploring the subjective quality of the habitat with PPGIS as well as findings on the discovered items of the habitat. The discussion section reflects upon the constraints in using PPGIS toolkit for the studies on the habitat and outlines its further perspectives.

Anastasiia Galaktionova, Aleksandra Nenko
Smart Technologies and Their Role in the Modernization of Non-motorized Urban Transport in Russia

The urban population growth and the negative impacts of the current car focused transport systems imply significant challenges with respect to environmental and social sustainability for governments and planners in cities. At the same time sustainable transport systems in combination with smart technologies could help in solving these challenges. This article is focused on the usage of these smart technologies in sustainable transport modes, such as bike sharing systems and smartphone applications. We discuss the main benefits and disadvantages of non-motorized individual transport i.e., cycling and walking, smart solutions used in cycling and walking and the results of a pilot survey among cyclists in St. Petersburg, Russia. The aim of this article is to present a short overview of existing smart solutions used by cyclist and pedestrians and carry out a short pilot survey about the usage and barriers of these smart solutions. It was found, that not all smart technologies are equally well used.

Lasse Schneider, Irina A. Shmeleva
Support for RoboCops: Measuring Effects of Attitudes Towards Police and Policing Technologies

Despite such an intensive spread of digital technologies in policing and law enforcement not too many studies have addressed citizens attitudes towards these shifts. If robots are to be introduced for performing policing function it is not only necessary to test whether they are effective in fulfilling their tasks, but also whether citizens perceive them as safe and capable of providing protection. We use data obtained from a sample of 570 students from the two large universities in the city of St. Petersburg, Russia to explore attitudes towards use of robots in street patrolling. Results show that young people are willing to accept surveillance in public places, but are unsupportive of online surveillance tools and regulations. Our research finds that half of the young citizens of St. Petersburg are supportive of robocops patrolling the streets. These positive attitudes are produced by fear of police and fear of victimization. They are enhanced by acceptance of other surveillance technologies (such as surveillance cameras) and willingness to use other digital innovations (such as accident-reporting apps and unmanned cars). When technology acceptance is not considered gender differences can be observed: compared to females, males have greater support for robots. Perceptions of police legitimacy are not related to attitudes to robots used for patrolling.

Anna Gurinskaya

eHumanities: Digital Education and Research Methods

Learning Hard or Hardly Learning: Smartphones in the University’s Classrooms

Mobile devices are the necessary part of equipment for the busy life of modern people. Recent studies revealed that students use mobile phones in the educational environment more and more often. But there is a gap in empirical works related to the issue of what exactly do Russian students do with their smartphones during the class and how is this smartphone use connected to their academic motivation. In this study authors aimed to examine different aspects of smartphone usage by Russian university students during class in association with academic motivation, satisfaction with education, and indicators of problematic smartphone use. The study involved 437 participants aged between 17 and 34 years, 70,02% female. The findings revealed that students who used smartphones for academic purposes had expressed intrinsic academic motivation and learning achievements. Generally, students had sooner positive intentions towards smartphone use during the class and tended to disclaim distracting forms of smartphone use. Results have shown that students who actively used smartphones while learning, less satisfied with their education. Problematic smartphone use had a strong association with distracting forms of smartphone use during the class.

Yuliya L. Proekt, Valeriya V. Khoroshikh, Alexandra N. Kosheleva, Violetta F. Lugovaya
Designing Educational Trajectories for Generation Z: Identifying Cognitive Factors

This article is based on the hypothesis that Generation Z’s propensity for undivided perception of digital and physical reality (phygital reality) and their fairly easy absorption of new learning formats, in particular blended learning, are interrelated. To prove the existence of this relationship, the authors, based on the methodology of social constructivism and interpretivism, put forward several hypotheses and conduct an empirical study. For a detailed analysis of the research topic the authors conduct three questionnaire polls among university students in St. Petersburg. The first survey is related to identifying the features of socialization of “digital natives”, the second - to identify the cognitive inclinations of Generation Z, the third - the choice of type of education (traditional/classroom, blended or distance learning). The results of the study confirm the main hypotheses of the study, which are that the characteristics of Generation Z make them maximally adapted to blended learning and that the propensity to blended learning is due to a number of factors, such as satisfaction with the content of disciplines, propensity for self-development, satisfaction with the organization of the educational process, work in the specialty after graduation, group work in classes and the use of sources recommended by the teacher. Factor and regression analysis conducted during the study confirms the data obtained.

Irina Tolstikova, Olga Ignatjeva, Konstantin Kondratenko, Alexander Pletnev
Attitudes Towards Digital Educational Technologies, Academic Motivation and Academic Achievements Among Russian University Students

The purpose of present research is to reveal and compare the relationship of attitudes towards the digital educational technologies (DET) with academic motivation and academic achievements in Russian university students. The sample includes 173 (61% - female) first- and second-year university students of different fields of study (Natural Sciences, Medicine, and Psychology). To determine the motivation of students’ educational activity, the “Academic motivation scales” questionnaire by T.O. Gordeeva et al. was used. To diagnose students’ attitudes towards DET, the authors’ questionnaire was developed. GPA was used to assess the academic achievements of last academic year. The descriptive statistics methods, coefficients Cronbach’ α and McDonald’s ω, the Spearman’s correlation analysis, and factor analysis (Varimax) were used for statistical analysis. Statistical processing was carried out in the R software environment for statistical computing and graphics, version 3.6.1., psych package version 1.9.6. Findings of our research showed that university students with more pronounced intrinsic academic motivation are more involved in the digital space in general and more involved in the use of DET, while more amotivated students, on the contrary, less involved in the digital space and in the use of DET. At the same time, higher performing students tend to be more involved in the digital space in general. However, there is a specificity of these relations in students from different field of study. The obtained data must be taken into account when DET are implemented in the educational programs for students of different fields of study, based on their psychological characteristics.

Irina Novikova, Polina Bychkova
The Role of Values in Academic Cheating at University Online

This study investigated the role of basic human values in explaining academic dishonesty among undergraduate students in Russia (N = 471) during the emergency online learning in 2020. It was hypothesized that higher levels of self-enhancement would be associated with higher levels of dishonest behavior and that values would partially explain the differences by field of study, controlling for gender, age, grade-point-average, and perceived severity of penalty. Descriptive analysis revealed high levels of two types of online academic dishonesty: using unauthorized sources at exams and allowing others to copy exam answers. Majors differed by how much they reported plagiarism and contract cheating. Students’ basic values were also different from the representative national sample. Regression analysis revealed that the effects of majors are not compensated fully by basic human values. Achievement and power values had an average predictive value for the types of dishonesty making up 24% of the explained variance. The results are discussed in terms of consistency and further use of results for curbing online academic dishonesty at university.

Anastasiia Vlasenko, Anna Shirokanova
Designing Workflow for Improving Literature Review Process Based on Co-citation Networks

Literature reviews are essential parts of every academic paper, and there are many tools, which are trying to suggest relevant articles and make the process of working with citations easier. Many of them offer to focus on just specific recommended papers or provide a general picture of the area without explanations or hints on how particular papers can help. Co-citation networks serve as a foundation of multiple useful methods for citation recommendations, enabling the analysis of the structure of the scientific field. However, existing instruments using them have a steep learning curve. In this paper, we present the workflow prototype to elicit and evaluate a set of heuristics employing co-citation network analysis in the literature review process. We performed a step-by-step analysis, including analysis of bibliographic data visualization service VOSviewer patterns of use, which allowed us to synthesize Job Stories for the specification of possible user needs for citation recommendation. We produced a set of heuristics for the analysis of co-citation networks based on Job Stories. The heuristics are then evaluated on the set of papers from two Human-Computer Interaction conferences to reflect on their applicability and usability. Our results can be used to inform more straightforward navigation through co-citation networks, possible design improvements of services for literature management and bibliographic data visualization, as well as a foundation for learning designs for enhancing academic writing skills.

Anastasiya Kuznetsova
Interpretable Machine Learning in Social Sciences: Use Cases and Limitations

The increasing use of intelligent technologies, the development and implementation of machine learning systems in various spheres of life require explaining machine learning-based decisions in such systems. This need for interpretation leads to the increasing development of new methods for interpreting machine learning models and their more intense use in real systems. The paper reviews existing studies with applications of the interpretable machine learning (IML) methods in social sciences and summarizes results using bibliometric analysis. In total, seven research topics were described based on 210 papers. Moreover, the paper discusses the opportunities, limitations, and challenges of the interpretable machine learning approach in social science research.

Alena Suvorova
Normalization Issues in Digital Literary Studies: Spelling, Literary Themes and Biographical Description of Writers

Digital literary studies are a branch of digital humanities, which deals with national or world literatures. In this paper, we discuss normalization issues which are crucial for compiling eCulture resources, designed for cultural analytics, social and literary studies, as well as various aspects of digital humanities. One of such resources is the Corpus of Russian short stories of 1900–1930s with the detailed information about Russian writers of the epoch in concern intended for stylometric, linguistic and literary studies of Russian prose. We see our task to create a literary resource based on a system approach to the literature of a certain time period, which implies inclusion into consideration literary texts of the maximum number of writers, who created their works in the given period, both well-known and peripheral. The paper concerns the problem of data normalization, which is a necessary requirement for statistical processing of data of any kind. We describe how we deal with the problem of different spelling, how we normalize manual annotation of literary themes made by an expert and how we tackle the problem of standardization of biographical descriptions of authors. The obtained normalized data can be used for various kinds of research in the field of literary studies, digital humanities, computational linguistics, and cultural heritage studies.

Tatiana Sherstinova, Margarita Kirina
Prototyping of a Client for Board Games Automated Testing and Analysis

The process of tabletop game design is a complex iterative process that involves many tasks. Given the development of the industry, Computer Aided and even Mixed Initiative Design (MID) practices appear more and more often. Moreover, the academic field produces a variety of tools relevant for game designer’s assistance. However, the question arises: to what extent these tools meet the needs of modern tabletop game designers and do they fit into the current structure of the board game development process. This work aims to identify tabletop game designers needs and based on them prototype tabletop game design assistant (TGDA). We conducted in-depth semi structured interviews with tabletop game designers and described needs with a Job Story framework. Then, we partially implemented and prototyped them within a Jumanji Game test case for reliable interactive system assessment (Wizard of Oz). Findings demonstrate that game designers do not use any specialized or academic tools, even though the tabletop game development requires computer assistance. We indicate several reasons for that and propose principles of close-to-end-user production approach for convenient and reliable development. We also provide list of uncovered tabletop game designers needs for future implementation together with overall TGDA system requirements and areas of potential academic interest regarding tabletop game design.

Vlada Krainikova

eCommunication: Online Discources and Attitudes

Automated Classification of Potentially Insulting Speech Acts on Social Network Sites

Insulting speech acts have become the subject of public discussion in the media, social media, the basis for speculation in political communication, and a working concept in the legal environment. The present research article explores insulting speech acts on the social network site “VKontakte” aiming to develop an algorithm for automatic classification of text data. We conducted semantic analysis of the text of “Article 5.61” of the Code of Administrative Offenses of the Russian Federation, which made it possible to formulate inclusion criteria for formal classification. We used three common word embeddings models (BERT, ELMo, and fastText) on the original Russian language dataset consisting of 4596 annotated messages perceived as insulting speech acts. General findings argue that even in a specialized dataset the share of messages that meet criteria of inclusion is negligible. This indicates a low probability of going to court on the fact of an administrative offense under Article 5.61 based on speech communication on social network sites, even though such communication is public in nature and is automatically recorded in writing. Machine learning text classifier based on BERT model showed best performance.

Liliya Komalova, Anna Glazkova, Dmitry Morozov, Rostislav Epifanov, Leonid Motovskikh, Ekaterina Mayorova
Following the Lead When Nothing is Certain? Exploring the Image of Russia in Kazakhstani and Ukrainian Digital News Media

International news plays an important role in shaping public opinion about the foreign policy and leadership of a country. Yet research shows that the bias in favor of the current political leadership is prevalent in foreign news coverage. In this study, we explore whether these assumptions hold in the case of digital news outlets in media systems outside of established democracies. We examine the representations of Russia in digital news streams of Kazakhstan and Ukraine based on a collection of news published by about 30 top news websites in each of the countries during 2018 (n = 2,339,583 news items). To study the coverage of Russia, we follow an approach combining topic modeling for extraction of news agendas and qualitative analysis of news framing. Then, we compare Kazakhstani and Ukrainian news agendas and their framing. The results suggest that digital news media in the selected cases follow expectations based on the research of offline media despite the transformations that happened in news production with the advance of the Internet.

Anastasia Prytkova, Sergei Pashakhin, Sergei Koltcov
Participation of Transnational Migrants in the Formation of the Host Country Image Through Mass Self-communication

This exploratory study focuses on the role of transnational migrants as stakeholders in the process of shaping the image of a place, in particular, the host country. We studied the content created by 10 Russian-speaking Instagram bloggers with migration background residing on different continents. Through the content-analysis of 441 posts published in 2018, we have found that Russian-speaking Instagram bloggers addressing global Russophone audiences paid a significant amount of attention to the dissemination of information about the host country. They covered several aspects of host country image, including climate and geography, history and culture, security and stability, representatives of the host society, and general quality of life in the host country. While the three first categories received almost exclusively positive evaluations, the last ones, rooted in the personal daily experience represent a more diverse and complex picture. Both the bloggers and their audiences form a story about the host countries, which, in turn, forms the mediated image of the countries in the minds of the audience.

Anna Smoliarova, Yuliya Taranova, Marianna Vagaitceva
Exploring the Parliamentary Discourse of the Russian Federation Using Topic Modeling Approach

The parliamentary discourse is the important component of the socio-political basis of modern society. The study of its characteristics can explain many social dynamics processes, for example, the activity and apathy of society at elections, as well as the features of civil society. Qualitative studies, based on sociological methodology and discourse analysis, can benefit greatly from automated topic mining provided by topic models such as latent Dirichlet allocation (LDA). In this paper we present the results of analysis the speeches of deputies of the State Duma of the Russian Federation (seven parliamentary sessions). The aim of our work was to find relation between the behavior of parties during parliamentary sessions and the public skepticism about the idea of a multiparty system as a basis of democracy.

Anna V. Chizhik, Dmitry A. Sergeyev
The Other Side of Deplatforming: Right-Wing Telegram in the Wake of Trump’s Twitter Ouster

Is banning political figures who propagate controversial political speech from mainstream social platforms an effective way to improve the health of the public debate? Looking at the most conspicuous case of an anti-mainstream politician’s deplatforming – Donald Trump’s ban from several major social media platforms in January 2021 – we explore the less immediate effects that such measures can have on a wider information ecosystem. Specifically, we analyze the right-wing segment of social platform Telegram that has reportedly seen an influx of politically conservative users as a result of Trump’s expulsion from the mainstream social media. We demonstrate that the largest right-wing communities on Telegram has seen a multifold increase in user base during the period of observation. Furthermore, we employ network analysis and topic modelling to uncover familiar structures, agendas, and media repertoires characteristic to right-wing ecosystems that exist on mainstream social media platforms. These findings suggest that deplatforming should not be seen as the ultimate solution to the problem of toxic speech, and that further research into fringe political communities emerging on alternative social media in response to perceived free speech suppression is needed.

Kirill Bryanov, Dina Vasina, Yulia Pankova, Victor Pakholkov

eEconomy: Challenges of the COVID-19 Pandemic

COVID-19 Pandemic Impact on Customer Loyalty Factors in Russian E-Commerce Market

The main objective of this paper is to explore the impact of the COVID-19 pandemic on customer loyalty factors in the Russian e-commerce market. The pandemic has dramatically changed consumer behavior in e-commerce. Russia’s e-commerce has grown significantly since 2020 due to the COVID-19 pandemic. The new customers entering the online market and an increase in online shopping frequency due to the quarantine are among the reasons for the growth in the financial value of Russia’s e-commerce. There was a 44% growth of the industry in 2020 compared to 2019. To explore the possible impact of the COVID-19 pandemic on customer loyalty factors, quantitative empirical data was gathered in 2019 and 2020, with 836 and 926 accurate observations respectively. Methods of exploratory factor analysis, confirmatory factor analysis, and the t-test were used to analyze the data along with the validity and reliability indices. After confirming the CFA model, nine constructs affecting consumer loyalty in 2019 and 2020 were examined to investigate possible changes in the mean values of their indicators. The results showed that factors Consumer satisfaction, Ease of making online purchases, e-WOM, and Number of reviews have a statistically significant difference in the mean value of the indicators between Pre- and the COVID-19 era. These findings can help Russian online business managers to adapt to changes in consumer behavior. To enhance e-WOM, having a platform to get customer feedback and understand their perception about the service and product is recommended.

Vera Rebiazina, Mehran Haddadi
Management and COVID-19: Digital Shift to Remote Work and Remote Management

The study is devoted to the digital shift in management, forced by the precautions during the COVID-19 pandemic. The purpose of this paper is to provide an understanding of remote management, its challenges and opportunities faced in remote working by digital natives, young undergraduate students. The bibliometric analysis with VOSviewer revealed five research avenues on remote management in 2018–2021, that are digital transformation, technologies and supply chain; consumer behaviour, ICT and small business; business innovations and COVID-19 challenges; Industry 4.0 and manufacturing; sustainability. The paper includes an exploratory study of the opinion of undergraduate students regarding modern management practices. Based on the results of the qualitative research, the authors identify key benefits and challenges of remote management for the employees, employers and organisations. The respondents consider that remote work format is a driver of positive and negative organisational change that impact different organisational aspects – decision making, communication, conflict, organisational culture, leadership and motivation. The paper discusses the results and raises new questions that further research needs to answer.

Araksya Mirakyan, Svetlana Berezka
Labor Demand and Supply Adaptation to the Pandemic-Induced Shock
Analysis of Online Recruitment Data in Novosibirsk region of Russia

In our paper we explore the development of labor market in Novosibirsk, a region of Russia’s Siberian Federal Okrug, during the unprecedented events of 2020. In this, we rely on digital representation of the market, collecting the data from several online sources. These are the three popular Russian online job-related portals that publish vacancy and resume ads: HeadHunter, ZarplataRu and TrudVsem. We devise the joint taxonomy for the three somehow discordant portals to better cover the regional specifics and reveal the balance between workforce demand and supply in various industries in 2017–2020. The results of our analysis suggest while the supply, as manifested in resume ads, had short-term flexibility, no remarkable changes were noted in the demand. However, vacancies better reflect the situation in the labor market, even though the wages they propose were only 77.1% of the official wages for the region. The discovered lack of correlation between the numbers of the ads and the wages in the ads suggests that online recruitment is not competitive. Also, at least in the considered region, the recruitment through job-related portals largely involves straightforward and immediate hiring for less qualified and lower paid positions.

Irina Sizova, Maxim Bakaev, Vladimir Khvorostov
How has the COVID-19 Pandemic Transformed the E-Commerce Market on the Firm Level: Qualitative Insights from the Russian Market

Due to markets’ digitalization, both consumers and businesses are increasingly involved in e-commerce activities throughout the globe. Current study aims to investigate what drives and what limits firms’ integration into e-commerce activities with the focus on comparison of pre-, during and post-pandemic foci by the firms in Russian emerging market. The study is based on insights from qualitative interviews of firms’ representatives, collected in 2016 and 2021. Based on comparison of interview’s insights and content analysis, we identified the influencing factors from the firms’ perspective, further we also introduced potential consequences of the pandemic based on the respondents’ replies. One contribution of this study is to identify the limiting and the driving factors that are specific for the Russian e-commerce market. Besides, we discover some factors that can supplement the current frameworks for structuring the limiting and the driving factors of the e-commerce market. In addition to that, based on the theoretical and empirical research conducted, we can state that the factors influencing e-commerce five years ago and now are evolving rapidly and may lead to more prominent changes.

Megi Gogua, Vera Rebiazina, Maria Smirnova

eEconomy: E-Commerce Research

Fast-Growing eCommerce and Omnichannel Concept Development: Empirical Evidence from Russian Retail

The omnichannel business model is becoming increasingly popular nowadays. The COVID-19 crisis has strongly influenced consumer behavior, with the role of e-commerce becoming ever more important. The “new normal” requires that retailers adapt quickly in order to, on the one hand, satisfy consumer needs in the most appropriate way and, on the other, maintain their competitive advantage in the market. This study aims to identify and analyze the omnichannel activities of retailers in order to provide a concept of the development of a short-term omnichannel business model under pressure of the crisis. The research found that the COVID-19 crisis has boosted the development of the omnichannel model in retail. The research suggests the following step-by-step measures for implementation of the omnichannel approach have been adopted: introduction and expansion of online shops and delivery services; immediate response to customers’ needs and purchase barriers; establishment of an automatization process inside the company; alignment of company strategies with omnichannel model development; further development of omnichannel strategy via collaboration mechanisms; and improvement of category management & consumer-oriented factors. The study provides retailers’ reflections on the new ways of operating, and suggests how the omnichannel development concept may be driven by external factors, as well as proposing opportunities for further research in the development of the omnichannel concept: detailed analysis of omnichannel strategies, or further steps in medium-term omnichannel development after the pandemic period. This research offers practical guidance to managers in retail companies, such as the step-by-step omnichannel business model implementation approach.

Oksana Piskunova
Using Triple Exponential Smoothing and Autoregressive Models to Mining Equipment Details Sales Forecast

Stock planning is an essential part of supply management. Mistaken planning can lead to high costs and expenses. So, the correct plans are required, which should satisfy sales demand at any time. Forecasting is one of the planning techniques. This paper aims to present the sales forecasting models for the mining equipment details based on the historical sales data for two years. To this end, the triple exponential smoothing (Holt-Winters) and integrated autoregressive moving average (ARIMA) methods are used. To create periodic time-series for each detail the original data set is grouped by month. Defined time series are segregated into training and test data sets. Models for each detail are built using automated parameters selection in a such way to make absolute percentage error (APE) of the model minimized. Each model is followed by visualized plot graphs, which simplify the model and original data comparison. Achieved results demonstrate high average performance (95% for Holt-Winters, 93% for ARIMA). Built algorithms can be used in practical conditions for equipment forecasting.

Kirill Kashtanov, Alexey Kashevnik, Nikolay Shilov
Facilitating Adoption of B2B e-Commerce Platforms

Currently there is a lot of research that stresses the importance of customer relationship management based on the development of e-commerce platforms. However, when we make the transition to the b2b market we are faced with problems of customer adoption of such systems. Even though we live in a digital era with the recent pandemic forcing the shift to online processes, many companies still prefer to deal with real people and company representatives. The aim of the present research is to reveal and analyze factors that contribute to adoption of e-commerce systems in b2b markets and give recommendations on how to engage partners in it without losing revenues and clients. The methodology includes an analysis of answers of 329 respondents who have used the e-commerce b2b platform in the last 6 months. Data analysis was done with structural modeling that helped to understand the main drivers of e-commerce system adoption.

Anastasiia Berezina, Ekaterina Buzulukova, Olga Tretyak
Worker’s Motivation and Planning Strategies on Crowdsourcing Platforms. The Case of Yandex Toloka

The analysis of the crowdsourcing platform Yandex Toloka started from the investigation text reviews about the work on the platform. Ed text reviews were analysed using the Structural Topic Modelling approach and Biterm Topic Modelling. Performed text analysis of negative and positive reviews revealed that microworkers deliver their attention to the underpayment problem, to the problems connected with not enough working experience, lacking the skills or personal characteristics such as lacking the patience or assiduity.

Elizaveta Danilova
Digital Transformation and Global Society
Daniel A. Alexandrov
Alexander V. Boukhanovsky
Andrei V. Chugunov
Yury Kabanov
Olessia Koltsova
Ilya Musabirov
Sergei Pashakhin
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