Abstract This paper focuses on methods of machine learning, particularly on regression analysis to solve a problem of authority identification within social networks. Within this paper, linear, polynomial, and non-linear regression types were considered. The aim was to find an approximation of dependency of the authority value on variables representing parameters of the structure and particularly the content of selected web discussions. The approximation function can be used at first for computation of the authority value of a given discussant, at second, for discrimination of an authoritative discussant from non-authoritative contributors to the web discussion. This information is important for web users, who search for truthful and reliable information in the process of decision making about important things. The web users would like to be influenced by some credible professionals. The various regression methods were tested, particularly linear, polynomial, and non-linear regression models. The best solution was implemented in the Application for the Machine Authority Identification.
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