Determination of Young Generation’s Sensitivity to the Destructive Stimuli based on the Information in Social Networks

Alexander Branitskiy1, Dmitry Levshun1, Natalia Krasilnikova2, Elena Doynikova1, Igor Kotenko1+,
Artem Tishkov2, Nina Vanchakova2, and Andrey Chechulin1

 

1St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St.Petersburg, Russia

{branitskiy, levshun, doynikova, ivkote, chechulin}@comsec.spb.ru

2Pavlov First Saint Petersburg State Medical University, St.Petersburg, Russia

NataljaKrasilnikova@yandex.ru, {artem.tishkov, nvanchakova}@gmail.com

 

 

Abstract

The paper describes the developed technique to determination of young generation’s sensitivity to the destructive stimuli based on the information provided by its representatives in the social networks. The technique uses the methods of neural network processing of Internet content. The underlying approach integrates the technologies of psychological examination and artificial intelligence. It allows overcoming the challenge of manual processing of the huge amount of information. The proposed technique can be further used for detection of destructive impacts in the Internet space and monitoring of influence of these impacts on the social networks’ users. The paper shows the place of the technique in this task. Implementation of the proposed technique for determination of sensitivity of social networks’ users to destructive stimuli is described. The experiments that demonstrate existence of the relation between information users provide in social networks and their sensitivity to destructive stimuli are conducted and their results are analyzed.

Keywords: social network, detection of destructive information impacts, stimuli, neural network,

sensitivity of young generation to destructive, Ammon’s test, user profile, psychological scales

 

+: Corresponding author: Igor Kotenko
14-th Liniya, St.Petersburg, 199178, Russia, Email: ivkote1@mail.ru, Tel: +7-812-328-7181

Journal of Internet Services and Information Security (JISIS), 9(3): 1-20, August 2019

DOI: 10.22667/JISIS.2019.08.31.001 [pdf]