Dean — Andrey Starodubtsev
Adress: 123 Naberezhnaya Kanala Griboedova
This paper investigates to what extent activity of a social movement on a social networking site is related to participation in offline collective action. Through this research, we seek to contribute to a broader theory of effective communicative structures of social movements. We use the data of roughly 12,000 individuals from 17 online groups representing the branches of the ‘Observers for Fair Elections’ movement in 17 districts of St. Petersburg, Russia, and compare their online properties to real offline participation of movement members in elections in the role of electoral observers. We find that while prediction of individual offline participation with this online data is of limited power, association between district participation rates and online group features is very strong. Large, more inclusive and evenly connected networks, where people are engaged in high-threshold online activities, produce more offline participants; weak individual-level prediction, combined with strong group-level prediction, suggests either the presence of the ‘network effect’ or of third factors – such as prior contentious experience or the effect of leaders.
In the second quarter of the 20th-century Russian émigré philosopher Georgii Fedotov coined the description of a personality type termed the “Russian European”. He distinguished the creative type of “Russian Europeans” loyal to both Russian and European cultural values from two other negative types: the “autocratic-despot” and “anti-state-nihilist”. In this chapter I look at how this concept was further theorised in works of Vladimir Kantor and Alexei Kara-Murza and relate it to an anti-war message developed in a 2002 Russian film The Cuckoo.
Interpreting The Cuckoo this chapter, in particular, shows how various scenes from the movie overlap with ideas of “dialogism” and help to deconstruct what Mikhail Bakhtin called an “authoritative discourse”. I also explore how concepts like “life knowledge” and “all-unity” (by Semyon Frank) enable us to speak up against war and political violence today.
Online social networks (OSNs) play an increasingly important role in news dissemination and consumption, attracting such traditional media outlets as TV channels with growing online audiences. Online news streams require appropriate instruments for analysis. One of such tools is topic modeling (TM). However, TM has a set of limitations (the problem of topic number choice and the algorithm instability, among others) that must be addressed specifically for the task of sociological online news analysis. In this paper, we propose a full-cycle methodology for such study: from choosing the optimal topic number to the extraction of stable topics and analysis of TM results. We illustrate it with an analysis of online news stream of 164,426 messages formed by twelve national TV channels during a one-year period in a leading Russian OSN. We show that our method can easily reveal associations between news topics and user feedback, including sharing behavior. Additionally, we show how uneven distribution of document quantities and lengths over classes (TV channels) could affect TM results.
This essay examines the quantitative aspects of Greco-Roman science, represented by a group of established disciplines that since the fourth century b.c.e. had been called mathēmata or mathēmatikai epistēmai. Among the mathēmata, which in antiquity normally comprised mathematics, mathematical astronomy, harmonics, mechanics, and optics, the essay also includes geography. Using a data set based on The Encyclopaedia of Ancient Natural Scientists, it considers a community of mathēmatikoi (as they called themselves), or ancient scientists (as they are defined for the purposes of this essay), from a sociological point of view, focusing on the size of the scientific population known to us and its disciplinary, temporal, and geographical distribution. A diachronic comparison of neighboring and partly overlapping communities—ancient scientists and philosophers—allows the pattern of their interrelationship to be traced. An examination of centers of science throughout ancient history reveals that there were five major sites—Athens, Alexandria, Rhodes, Rome, and Byzantium/Constantinople—that appeared, in succession, as leaders. These conclusions serve to reopen the issue of the place of mathēmata and mathēmatikoi in ancient society.
This article explores the relationship between educational outcomes and anti-school attitudes at different levels of social organization in schools. Data were collected in St. Petersburg, Russia (104 schools, 7300 students) and analyzed using multi-level regression models that included three levels: individual, clique of friends and school. A clique is defined as a tight group of friends in a school class; we used social network analysis software Kliquefinder for clique identification. We demonstrate that friends’ attitudes are strongly related to the educational outcomes of a student (net of person’s individual attitudes and socio-demographic characteristics). In contrast, school-level effects disappear in the multi-level model when individual characteristics are included. The results of the study clearly demonstrate that the socio-economic and curricular differentiation of schools does not always lead to the polarization of ‘school academic cultures’. A school social environment is sufficiently heterogeneous, and different value systems in small peer groups may coexist.
This study proposes to minimize Rényi and Tsallis entropies for finding the optimal number of topics T in topic modeling (TM). A promising tool to obtain knowledge about large text collections, TM is a method whose properties are underresearched; in particular, parameter optimization in such models has been hindered by the use of monotonous quality functions with no clear thresholds. In this research, topic models obtained from large text collections are viewed as nonequilibrium complex systems where the number of topics is regarded as an equivalent of temperature. This allows calculating free energy of such systems—a value through which both Rényi and Tsallis entropies are easily expressed. Numerical experiments with four TM algorithms and two text collections show that both entropies as functions of the number of topics yield clear minima in the middle area of the range of T. On the marked-up dataset the minima of three algorithms correspond to the value of T detected by humans. It is concluded that Tsallis and especially Rényi entropy can be used for T optimization instead of Shannon entropy that decreases even when T becomes obviously excessive. Additionally, some algorithms are found to be better suited for revealing local entropy minima. Finally, we test whether the overall content of all topics taken together is resistant to the change of T and find out that this dependence has a quasi-periodic structure which demands further research.
As well as the most areas of social life, the field of art is now extended to the cyberspace. In this study, we analyze online reviews of Russian art critics with two objectives. On the one hand, we investigate the patterns of the interactions between critics and artists (both contemporary and recognized ones) in the Russian Art. Since the Russian school of art critique is still in the process of formation, an analysis of web data we offer a significant contribution to the scope of Russian Art studies. On the other hand, we use social network analysis and text mining tools in order to gain more insights from the data and affirm the applicability of the modern tools to the classic research tasks. In this study we analyze data from the 5 Russian art magazines, in particular articles, authors and named entities from this texts. As a result, we explored different patterns of the critics production that could divide this area of web interaction both by geographical and textual characteristics of agents and article
Quality of life and one’s subjective evaluation of one’s own happiness and well-being are the conventional focus of psychology and sociology. However, a genetic factor has recently been found to affect the subjective evaluation of well-being. The contribution of heredity to a personal level of happiness and life satisfaction has been estimated at 30–50% in twin studies. Individual genes associated with these traits have been identified, but the available data are rather discrepant. In this work, alleles of the monoamine oxidase A gene (MAOA) were tested for association with well-being components, such as happiness, health, dangers of living environment, and stress, in Russian men. Trait assessments were based on questionnaires filled out as part of the World Values Survey. It is shown that, among the uVNTR-3R allele carriers, the proportion of men who have high levels of stress, feel unhappy, and live in unsafe environments is lower. The results are discussed in the context of the gene plasticity concept, which provides a possible explanation for how expression of genes related to behavior changes in different environmental conditions.
Contrary to the popular narrative of ‘return’, the spheres of influence that have destabilized Ukraine are not a throwback to the nineteenth century. They are something new. What makes them new is explained here in a story of a failed experiment to escape geopolitics in a region between the borders of an enlarged European Union (EU) and Russia. This project created a ‘grey zone’ of overlapping authority, jurisdiction and allegiance out of which new spheres of influence emerged. Ukraine’s geopolitical misfortune was to be included into this ‘grey zone’. The logic of this new narrative of the Ukraine crisis is worked out with reference to the literature on neo-medievalism – a political theory that develops a critique of supranational projects like European integration.
The article describes the current model of intergovernmental relations in Russia and explains how it was formed in the 2000s, as well as demonstrating its effects in one sphere of public administration, namely education. Based on theoretical perspectives on the expected and unexpected effects of decentralization, authoritarian politicians’ motives and central governments’ strategies aimed at overcoming the principal-agency problem, the author hypothesizes that decentralization realized under the conditions of an authoritarian government in geographically, ethnically and economically complex societies produces a kind of trap: concentration on administrative decentralization intensifies the principal-agency problem while the authoritarian rulers’ interests limit the potential for employing effective means to overcome it.
Despite the increasing number of studies devoted to creative professionals, there are still many topics, which remain understudied. Among these topics there is interconnection of professional labor and cultural institutions of which labor conditions are framed. Furthermore, while much research has been devoted to the UK, other regions or global concerns have gained little attention. This article concerns creative professionals in post-Soviet Russia. It offers an overview of the field of cultural institutions in St. Petersburg in relation with the cultural administration and the professionals working for it. In particular, this study points out to the public sector in the Russian cultural production and new non-state institutions founded by young entrepreneurs and activists, which have constantly to struggle for recognition and support of the city’s administration. Based on fieldwork conducted in St. Petersburg in 2012-2014, the empirical study includes 26 in-depth interviews with cultural managers, employees of art-centers, lofts, creative spaces, museums, theatres. The research items here highlighted are concerned with the peculiarities of the institutional environment arisen in Russia as regards the creative labor in public and non-governmental cultural institutions. It is discussed whether the post-socialism system presents a ‘luckier’ medium for a ‘good’ creative job than that of advanced capitalism.
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
This two volume set (CCIS 858 and CCIS 859) constitutes the refereed proceedings of the Third International Conference on Digital Transformation and Global Society, DTGS 2018, held in St. Petersburg, Russia, in May/June 2018.
The 75 revised full papers and the one short paper presented in the two volumes were carefully reviewed and selected from 222 submissions. The papers are organized in topical sections on e-polity: smart governance and e-participation, politics and activism in the cyberspace, law and regulation; e-city: smart cities and urban planning; e-economy: IT and new markets; e-society: social informatics, digital divides; e-communication: discussions and perceptions on the social media; e-humanities: arts and culture; International Workshop on Internet Psychology; International Workshop on Computational Linguistics.
In the early 1990s, the Russian public held overwhelmingly favorable attitudes toward the United States; in recent years, attitudes toward the United States have been overwhelmingly unfavorable. Analysts often trace this dramatic change to (1) the emergence of Russian-American conflicts such as those in former Yugoslavia and (2) Russian leaders’ attempts to escape blame for their country’s failures by attributing them to a powerful external enemy. We point to another major factor of Russian anti-Americanism that preceded the international conflicts and the government-led anti-American propaganda: (3) disillusionment, or an emotional and ideological dissatisfaction with the outcome of pro-Western reforms that started among the liberal elites and then spread among the general public. Using data from the New Russian Barometer surveys, we analyze the dynamics of attitudes toward the United States from 1993 to 2009. We find that mass disappointment in the perestroika outcomes preceded the spread of anti-Americanism in Russia and that anti-American sentiment was stronger and occurred earlier among the elite than among the mass public. Furthermore, those (especially better-educated) people who express disappointment with the outcomes of pro-Western reforms prove significantly more anti-American. Our findings illustrate a general ideological phenomenon that may explain the growth of anti-Americanism in unsuccessful democracies worldwide.
We use social media and WWW data to analyse international educational migration from Russia. We find substantial regional differences in migration patterns for three contrast directions: the Nordic countries, China and the Middle East. We built a model of migration flows with geographic distances to destination countries, various socio-demographic data and institutional characteristics of educational organisations.