Precedent-Based Approach for the Identification of Deviant Behavior in Social Media

Abstract

The current paper is devoted to a problem of deviant users’ identification in social media. For this purpose, each user of social media source should be described through a profile that aggregates open information about him/her within the special structure. Aggregated user profiles are formally described in terms of multivariate random process. The special emphasis in the paper is made on methods for identifying of users with certain on a base of few precedents and control the quality of search results. Experimental study shows the implementation of described methods for the case of commercial usage of the personal account in social media.