Behavioral Analysis of Social Networks’ Users Based on Machine Learning Methods

Student: Razumova Inna

Faculty: St.Petersburg School of Economics and Management

Educational Programme: Big Data Analysis for Business, Economy, and Society (Master)

Final Grade: 8

Year of Graduation: 2018

Social networks are an integral part of modern society: they allow us to communicate with friends and colleagues, transfer information without delay, and spend some leisure time. The main motivation for this pastime is various social interactions. These interactions can be considered as two-sided, if at least two users are involved, or one-way, if the user spends time on the social network, without communicating with other users. In the absence of communication with other users, users have passive communications, for example, with communities. In this paper, a method is proposed for maintaining user loyalty to a social network: a system that recommends some communities to users based on the activity of the user and his current communities.

Full text (added May 31, 2018)

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