Research into the Algorithms for Opinion Leaders Identification in Social Networks Using Machine Learning Techniques

Student: Semenkovich Sofia

Educational Programme: Electronic Business (Master)

Year of Graduation: 2019

The present paper is dedicated to development of an algorithm of opinion leaders identification in social networks using machine learning methods. The main applications of machine learning algorithms for social network analysis are discussed, examples of existing opinion leaders search algorithms and their advantages and disadvantages are given. A modified algorithm for finding the most influential social network nodes, which takes into account not only the position of the node in the network, but also signs of its activity, such as the number of posts, the number of comments and the number of reposts is proposed. The developed algorithm is more accurate than the algorithm, which is based only on the position of the node in the network. Limitations of using the algorithms as well as possible problems with machine learning application in the field of social network analysis are described.

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