STUDY OF THE INFORMATION FIELD BASED ON THE DYNAMIC APPROACH TO THE DATA ANALYSIS OF THE SOCIAL NETWORK «VKONTAKTE» (TOMSK CASE)

Abstract

The paper considers the potential of a dynamic data analysis approach in studying user behavior in social networks. Currently, information appears on social networks that allows differentiating user groups by their activity within the technical capabilities of a particular social network. The paper introduces the description, a brief analysis of the information field in the regional communities of the Tomsk region; the clustering of posts into three spheres of the life of society: social, economic and political, is formed. Methodology. A dynamic approach was used to analyze social media data. The analysis of user behavior, the structure of nodes and connections of social networks is carried out, which makes it possible to identify the rate of growth or decrease in the size of the network, the redistribution of connections between groups. After receiving a list of informative and unique posts, a semantic analysis of the texts was performed using the PolyAnalyst text analytics tool. Results. The semantic connections between words were built and presented in the form of graphs. Two «centers» are highlighted that connect all the most frequently encountered words – Tomsk and Tomsk Oblast. Popular people and organizations are highlighted using the PolyAnalyst text analytics tool. The greatest positive content was recorded in the coverage of the Safe and High-Quality Roads program in the region in the social network to form a positive media image of the authorities in the region. Socially active users draw attention to social topics. So, among the most popular posts, the largest number is devoted to the social sphere, followed by the political and economic. At the same time, social networks are also a currently available tool for manipulating public opinion.

Keywords

• dynamic approach
• data analysis
• social networks
• regional communities