Virtual caucasus on VK social networking site

Alexandrov, Daniel; Gorgadze, Aleksei; Musabirov, Ilya

doi:10.1145/2908131.2908205

Cited by 3 publications

(3 citation statements)

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“…for mining topics in legislative speeches (Quinn et al, 2010) or abstracts of scientific papers (Diesner & Carley, 2010). However, more recently it has been successfully applied for mining topical structure in the Russian-language blogs (Koltsova & Koltcov 2013;Koltsova & Shcherbak, 2015) and group pages in the Russian social networking site VKontakte (Voskresenskiy et al, 2015;Alexandrov et al, 2016). These algorithms ascribe each word and each text to a number of latent variables topicswith varying probabilities and thus may be viewed as methods of fuzzy co-clustering of words and texts over topics.…”

Section: Topic Modeling and Sentiment Analysis For Social Problems Rementioning

confidence: 99%

Mining Media Topics Perceived as Social Problems by Online Audiences: Use of a Data Mining Approach in Sociology

Stanislavovich

Koltsova

2017

SSRN Journal

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Media audiences that represent a significant part of a county's public may hold opinions on mediagenerated 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.

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Section: Topic Modeling and Sentiment Analysis For Social Problems Rementioning

confidence: 99%

Mining Media Topics Perceived as Social Problems by Online Audiences: Use of a Data Mining Approach in Sociology

Stanislavovich

Koltsova

2017

SSRN Journal

View full text Add to dashboard Cite

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“…Тематическое моделирование уже успешно использовалось для выявления тем этнических текстов [Alexandrov, Gorgadze, Musabirov, 2016;Apishev et al, 2016;Nikolenko, Koltcov, Koltsova, 2017].…”

Section: темы этнического дискурсаunclassified

“…В качестве примера можно привести статьи, авторы которых изуча ли различия в самопрезентации этнических групп в социальной сети Facebook [Grasmuck, Martin, Zhao, 2009] и при помощи анализа гиперссылок исследова ли, как Интернет повлиял на самопрезентацию этнических диаспор [Diminescu, Loveluck, 2014]. Российские социологи также не остались в стороне от этнических исследований в Интернете, сосредоточившись на изучении сообществ в россий ской социальной сети «ВКонтакте», где они исследовали конструирование татар ской идентичности [Suleymanova, 2009], выявляли и анализировали кластеры сети, построенной на основе членства пользователей «ВКонтакте» в кавказских группах [Alexandrov, Gorgadze, Musabirov, 2016].…”

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