The method of time reduction during anti-virus heuristic qualifier learning based on the expanded binary search algorithm usage

2017. №1, pp. 63-70

Azhmukhamedov Iskandar M - Sc. (Engineering), Associate Professor, Astrakhan State University,

Machueva Dina A. - postgraduate student, Astrakhan State Technical University, 16 Tatishchev St., Astrakhan, 414056, Russian Federation,

Zholobov Denis A. - Ph.D. (Engineering), Associate Professor, Astrakhan State University,

Social networks are an important socio-cultural phenomenon of our times. They are becoming a significant focus of research, allowing experts to study the special characteristics of social behavior in various segments of the population, and on that basis, to formulate policies of interaction with various organizations, political parties, etc. Communities existing in the social networks largely reflect the structure of society and are a comfortable environment for the implementation of informational influences and for the propagation of information. To meet the challenges of information management, researchers need to be able to simulate the process of information propagation in the social networks. In this article, a methodology is proposed for the determination of basic data for such a simulation, by constructing informational profiles of social networks users on the basis of their distribution according to key categories (such as gender, age, education, etc.), as well as according to their personal characteristics, which influence the information exchange process. These data are obtained by analyzing pages of users in the social networks, with the personal characteristics being evaluated with the help of a special questionnaire. A data collection methodology was tested based on the example of users of the social network "VKontakte" in one of the constituent entities of the Russian Federation, the Chechen Republic

Key words: социальная сеть, информационное воздействие, управление, процесс распространения информации, информационный профиль пользователей, парсинг, опрос, репрезентативная выборка, степень коммуникабельности, значимость мнений, social network, informational influ