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Cyberbullying detection and prevention: Data mining in social media

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dc.citedby1
dc.contributor.authorSultan D.en_US
dc.contributor.authorSuliman A.en_US
dc.contributor.authorToktarova A.en_US
dc.contributor.authorOmarov B.en_US
dc.contributor.authorMamikov S.en_US
dc.contributor.authorBeissenova G.en_US
dc.contributor.authorid57212005373en_US
dc.contributor.authorid25825739000en_US
dc.contributor.authorid57222724179en_US
dc.contributor.authorid57202103462en_US
dc.contributor.authorid57222723126en_US
dc.contributor.authorid57222119982en_US
dc.date.accessioned2023-05-29T09:09:20Z
dc.date.available2023-05-29T09:09:20Z
dc.date.issued2021
dc.descriptionCloud 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 miningen_US
dc.description.abstractThis 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 IEEEen_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9377077
dc.identifier.doi10.1109/Confluence51648.2021.9377077
dc.identifier.epage342
dc.identifier.scopus2-s2.0-85103813121
dc.identifier.spage338
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85103813121&doi=10.1109%2fConfluence51648.2021.9377077&partnerID=40&md5=c94ab8e2c85ef3426db6e74dd0c1ca72
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26344
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings of the Confluence 2021: 11th International Conference on Cloud Computing, Data Science and Engineering
dc.titleCyberbullying detection and prevention: Data mining in social mediaen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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