Application of automated collection of information from social network communities to identify active users

B. A. Nizomutdinov, L. A. Vidiasova


The article presents a method developed by the authors to determine the most active subscribers of communities in social networks. The object of study was 18 official groups of district administrations of St. Petersburg VKontakte. The paper describes the implementation of an algorithm for data collection and analysis. The study determined the total number of comments in each community and identified the most active subscribers who leave the most comments under posts. The analysis of socio-demographic characteristics of active users was carried out using automated tools for parsing social network data. All collected data has been depersonalized. The results of the study showed the existence in each community of a core of active users who leave the most reactions to posts published in groups. The conclusion is made about the great potential that can be extracted from the use of automated data collection from social networks.

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