Statistical model for the identification of target objects in a social network

D. I. Safikanov, A. A. Artamonov, Yu. E. Fomina, A. I. Cherkasskiy

Abstract


Taking into account the growing role of social media, their analysis is a topical issue in information technology. Its development can allow solving a wide range of applied tasks. However, when analyzing social networks, a number of problems arise related to the volume of data, their heterogeneity and unstructured nature. One of the ways to solve these issues is the use of agent technologies. The article describes the methodology of the use of statistical models for agent-based search of target objects, which involves the following actions. At the first stage, analysts form a training set of target objects through an interactive search in a social network. Then, the analysis of the training set is carried out in order to determine the evaluation criteria, rank them by importance and assign weight coefficients to them. As a result, a statistical model of the target object is formed. Based on the training sample, boundary values (markers) are determined for marking new objects as target ones. In the next step, agents are configured to automatically perform the target search. In the course of practical implementation, agent search has proved to be an effective tool for identifying target objects in a social network VKontakte. The proposed methodology can potentially be scaled for use in other social networks.


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