Tag topic modelling

Posts: 5

Digital Inequality in Russia through the Use of a Social Network Site: A Cross-Regional Comparison

An important role of digital inequality for hindering the development of civil society is being increasingly acknowledged. Simultaneously, differences in availability and the practices of use of social network sites (SNS) may be considered as major manifestations of such digital divide. While SNS are in principle highly convenient spaces for public discussion, lack of access or domination by socially insignificant small talk may indicate underdevelopment of the public sphere. At the same time, agenda differences between regions may signal about local problems. In this study we seek to find out whether regional digital divide exists in such a large country as Russia. We start from a theory of uneven modernization of Russia and use the data from its most popular SNSVK.com” as a proxy for measuring digital inequality. By analyzing user activity data from a sample of 77,000 users and texts from a carefully selected subsample of 36,000 users we conclude that regional level explains an extremely small share of variance in the overall variation of behavioral user data. A notable exception is attention to the topics of Islam and Ukraine. However, our data reveal that historically geographical penetration of “VK.com” proceeded from the regions considered the most modernized to those considered the most traditional. This finding supports the theory of uneven modernization, but it also shows that digital inequality is subject to change with time.


Mining media topics perceived as social problems by online audiences: use of a data mining approach in sociology

Media audiences that represent a significant part of a county’s public may hold opinions on media-generated definitions of social problems different from those of media professionals. The proliferation of user-generated content makes such opinions available, but simultaneously demands new automatic methods of analysis that media scholars still have to master. In this paper, we show how topics regarded as problematic by media consumers may be revealed and analyzed by social scientists with a combination of data mining methods. Our dataset consists of 33,877 news items and 258,121 comments from a sample of regional newspapers. With a number of new, but simple indices we find that issue salience in media texts and its popularity with audience diverge. We conclude that our approach can help communication scholars effectively detect both popular and negatively perceived topics as good proxies of social problems.


Репрезентация этничностей в русскоязычных социальных медиа

The paper presents the results of a study based on the Big Data para­digm analysis. The study aims at defining the features of the ethnic discourse in the Russian-­speaking social media and the place of the North Caucasus ethnic­ities in this discourse. The informational basis for the study is 2,659,849 social media publications containing ethno­nyms. The author concludes that the eth­nic discourse is full of problematic topics mainly discussed by male participants. The study shows that the ethnonyms re­lated to the North Caucasus peoples are often used in the context of crime and terrorism.