Detection and Monitoring of the Destructive Impacts in the Social Networks Using Machine Learning Methods-Reference-Cited by-同舟云学术

Detection and Monitoring of the Destructive Impacts in the Social Networks Using Machine Learning Methods

Published:2021 Issue: Volume: Page:60-65
ISSN:1865-0929
Container-title:ICT for Health, Accessibility and Wellbeing
language:
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Author:

Doynikova Elena^ORCID,Branitskiy Alexander^ORCID,Kotenko Igor^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-94209-0_6

Reference17 articles.

1. Social network Vkontakte. https://vk.com. Accessed 30 July 2021

2. Branitskiy, A., et al.: Determination of young generation’s sensitivity to the destructive stimuli based on the information in social networks. J. Internet Serv. Inf. Secur. (JISIS) 9(3), 1–20 (2019). https://doi.org/10.22667/JISIS.2019.08.31.001

3. Branitskiy, A., Doynikova, E., Kotenko, I.: Use of neural networks for forecasting of the exposure of social network users to destructive impacts. Inf. Control Syst. (1), 24–33 (2020). https://doi.org/10.31799/1684-8853-2020-1-24-33

4. Branitskiy, A., Doynikova, E., Kotenko, I.: Technique for classifying the social network profiles according to the psychological scales based on machine learning methods. J. Phys. Conf. Ser. 1864, 012121 (2020). https://doi.org/10.1088/1742-6596/1864/1/012121

5. Zlokazov, K.: Perception of the extremist text by subjects with different levels of destructive attitudes. In: Politicheskaya lingvistika, no. 1 (2014)

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