Open AccessMetric parameters of diffusion in destructive fillers automated networks
Author(s) -
I. Surkov,
Г.А. Остапенко,
V. Belonozhkin,
К А Разинкин
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/537/5/052018
Subject(s) - popularity , context (archaeology) , computer science , content (measure theory) , metric (unit) , social network (sociolinguistics) , content distribution , distribution (mathematics) , data mining , mathematics , engineering , world wide web , operations management , social media , psychology , mathematical analysis , social psychology , paleontology , computer network , biology
In this paper, a deep analysis was carried out and a classification of potentially destructive content and hazard metrics was obtained in an automated social network such as Instagram. The dependence effectiveness distribution of destructive content on the structural and functional specificity of a social network is determined. The classification of destructive content done in the Instagram social network allows us to determine the dependence popularity of various types destructive content on various parameters. The revealed dependence efficiency of the distribution of destructive content on the structural and functional specificity of a social network allows to design and implement the most effective organizational and technical measures to counteract the distribution of destructive content. Based on the above work, the owner of the automated network has the ability to influence the value of the network risk parameters in the context of the implementation of content wars.