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Abstract.
In this article, we present a web service designed for searching, extracting, and analyzing data from social networks and messengers, demonstrating its application for studying communities within the "VKontakte" social network. The web service enables the identification of typical user profiles within communities, the assessment of emotional sentiment in posts and comments, as well as the forecasting of community development trends. The described web service boasts extensive functional capabilities and an original neural network model for classifying texts of varying lengths based on emotional sentiment. Examples of the tool's usage are showcased in the analysis of the development of car brand communities. The analysis encompasses millions of subscriber audiences, tens of thousands of posts, and hundreds of thousands of comments, thereby affirming the relevance of the samples and the credibility of the results.
Keywords:
social network, communities, data analysis, neural network, profile, publication, emotional sentiment, tone, forecasting.
PP. 97-108.
DOI 10.14357/20718632240110
EDN YMIDVN References
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