Testing Methods for Processing Comments from Telegram Channels and Public VKontakte to Analyze the Social Media

Boris A. Nizomutdinov, Olga G. Filatova


The paper presents a comparative analysis of two official sources of information, using the example of a group in the social network VKontakte and the Telegram channel of the head of the Irkutsk region. The object of research is the comments that are published under official records and posts. Automated methods for collecting and processing comments were used. The VKontakte API and the Telescrape library were used to parse data from Telegram. The functionality of the desktop version of the Telegram messenger made it possible to upload comments from any open channel in JSON format. All the results obtained were saved in the Yandex Data Leans BI system. For the collected information, thematic modeling was carried out, 10 main topics were identified, which are discussed in the comments on VKontakte and on Telegram. The Gensim model of the Python library was used to create thematic models.  A comparative analysis of the selected topics showed that in the comments on VKontakte and on Telegram, different socio-economic problems raised by the inhabitants of the region are noticeable and they are ranked differently. The methods and approaches used, in general, have shown their effectiveness as an analytical tool for collecting and evaluating comments from different types of social media, which, in particular, makes it possible to identify their deliberative potential.

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