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Cyberbullying detection and prevention: Data mining in social media

Cloud computing; Computer crime; Data Science; Deep learning; Learning algorithms; Social networking (online); Children and adolescents; Cyber bullying; England; European Countries; Real time; Social media; Training machines; Data mining

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Bibliographic Details
Main Authors: Sultan D., Suliman A., Toktarova A., Omarov B., Mamikov S., Beissenova G.
Other Authors: 57212005373
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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id my.uniten.dspace-26344
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spelling my.uniten.dspace-263442023-05-29T17:09:20Z Cyberbullying detection and prevention: Data mining in social media Sultan D. Suliman A. Toktarova A. Omarov B. Mamikov S. Beissenova G. 57212005373 25825739000 57222724179 57202103462 57222723126 57222119982 Cloud computing; Computer crime; Data Science; Deep learning; Learning algorithms; Social networking (online); Children and adolescents; Cyber bullying; England; European Countries; Real time; Social media; Training machines; Data mining This article is devoted to analysis of the articles on cyberbullying of children and adolescents and creating the methodology of working on the own work, which related especially to Kazakh social media. The article provides examples of similar works by foreign researchers, the United States, England and other European countries. Using the methods of theoretical, namely analysis, synthesis, and empirical: comparison and experiment, the analysis of works on this topic was carried out, and this work was aimed at analyzing the problem in the Kazakh space. In brief, we consider the issue of creating a parser, as well as collecting data for training machine learning and deep learning algorithms that could find and block texts containing a humiliating slope in real time. The article will be of interest to both novice specialists who are engaged in data analysis, and experienced ones to expand their horizons. The question of implementing deep learning algorithms requires further study, which is one of the parts of a large work being done, as well as a future topic for a subsequent article. � 2021 IEEE Final 2023-05-29T09:09:20Z 2023-05-29T09:09:20Z 2021 Conference Paper 10.1109/Confluence51648.2021.9377077 2-s2.0-85103813121 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103813121&doi=10.1109%2fConfluence51648.2021.9377077&partnerID=40&md5=c94ab8e2c85ef3426db6e74dd0c1ca72 https://irepository.uniten.edu.my/handle/123456789/26344 9377077 338 342 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Cloud computing; Computer crime; Data Science; Deep learning; Learning algorithms; Social networking (online); Children and adolescents; Cyber bullying; England; European Countries; Real time; Social media; Training machines; Data mining
author2 57212005373
author_facet 57212005373
Sultan D.
Suliman A.
Toktarova A.
Omarov B.
Mamikov S.
Beissenova G.
format Conference Paper
author Sultan D.
Suliman A.
Toktarova A.
Omarov B.
Mamikov S.
Beissenova G.
spellingShingle Sultan D.
Suliman A.
Toktarova A.
Omarov B.
Mamikov S.
Beissenova G.
Cyberbullying detection and prevention: Data mining in social media
author_sort Sultan D.
title Cyberbullying detection and prevention: Data mining in social media
title_short Cyberbullying detection and prevention: Data mining in social media
title_full Cyberbullying detection and prevention: Data mining in social media
title_fullStr Cyberbullying detection and prevention: Data mining in social media
title_full_unstemmed Cyberbullying detection and prevention: Data mining in social media
title_sort cyberbullying detection and prevention: data mining in social media
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806424227166814208
score 13.214268

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