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Cybernetics and programming
Reference:

Analysis of the dynamic characteristics for target groups of social networks
Ipatov Yurii Arkad'evich

PhD in Technical Science

Associate Professor of the Department of Informatics at the Volga State University of Technology

424000, Russia, Mari El, Yoshkar-Ola, pl. Lenina, d. 3

philsilver@mail.ru
Другие публикации этого автора
 

 
Kalagin Ivan Vladimirovich

Student, Department of Сomputer Science and System Programming, Volga State University of Technology

424000, Russia, Respublika Marii El, g. Ioshkar-Ola, pl. Lenina, 3

lulldev@yandex.ru

Abstract.

The object of research is the dynamic characteristics for target groups of social networks. The subject of this study is to analyze the methods and models of the evolutionary characteristics of the social graphs of large dimension. The study examines in detail the approaches of analysis, quantitative characteristics graph models. Synthesized an algorithm to analyze the dynamic characteristics for target groups of social networks. The experimental results show the fact of adding a user to the subject area of interest, as well as visualize the entire process in real time. The developed software tools can be useful for further development and research topics related to the social network. When solving tasks used methods of mathematical logic, graph theory, mathematical statistics, the apparatus of mathematical analysis, linear algebra, mathematical modeling methods, theory of algorithms, as well as object-oriented programming techniques. The novelty of the study is to determine the dynamic characteristics of the target groups of social networks, as well as the visualization of the entire process in real time. The main conclusions of the study is that the developed software tool will enable to trace cause and effect indicators of changes in the social graph. The proposed prototype of the software will be of interest primarily marketers, system analysts, and professionals involved in the analysis and the study of social networks.

Keywords: characteristics social graph, social graph model, network analysis methods, dynamic network analysis, network evolution, Social network, graph visualization, group influence, conversion tool, social groups dynamics

DOI:

10.25136/2306-4196.2019.1.18417

Article was received:

20-03-2016


Review date:

21-03-2016


Publish date:

04-03-2019


This article written in Russian. You can find full text of article in Russian here .

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