Deep Learning Algorithms for Cyber-Bulling Detection in Social Media Platforms
Social media platforms are among the most widely used means of communication. However, some individuals exploit these platforms for nefarious purposes, with "cyberbullying" being particularly prevalent. Cyberbullying, which involves using electronic means to harass or harm others, is espec...
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| Veröffentlicht in: | IEEE access 2024, Vol.12, p.76901-76908 |
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| creator | Obaida, Mohammed Hussein Elkaffas, Saleh Mesbah Guirguis, Shawkat Kamal |
| description | Social media platforms are among the most widely used means of communication. However, some individuals exploit these platforms for nefarious purposes, with "cyberbullying" being particularly prevalent. Cyberbullying, which involves using electronic means to harass or harm others, is especially common among young people. Consequently, this study aims to propose a model for detecting cyberbullying using a deep learning algorithm. Three datasets from Twitter, Instagram, and Facebook were utilized to predict instances of bullying using the Long Short-Term Memory (LSTM) method. The results obtained revealed the development of an effective model for detecting cyberbullying, addressing challenges faced by previous cyberbullying detection techniques. The model achieved accuracies of approximately 96.64%, 94.49%, and 91.26% for the Twitter, Instagram, and Facebook datasets, respectively. |
| doi_str_mv | 10.1109/ACCESS.2024.3406595 |
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The model achieved accuracies of approximately 96.64%, 94.49%, and 91.26% for the Twitter, Instagram, and Facebook datasets, respectively.</description><subject>Algorithms</subject><subject>Blogs</subject><subject>Bullying</subject><subject>Convolutional neural networks</subject><subject>Cyberbullying</subject><subject>Datasets</subject><subject>Deep learning</subject><subject>Digital media</subject><subject>Hate speech</subject><subject>Long short term memory</subject><subject>LSTM</subject><subject>Machine learning</subject><subject>Social networking (online)</subject><subject>Social networks</subject><subject>Support vector machines</subject><subject>Young adults</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1PwzAMrRBITGO_AA6VOHfEddM2x9ENmDQ-pME5SlN3ZOqakXaH_XtaOqH5Ysv2e8_W87xbYFMAJh5mWbZYr6chC6MpRizmgl94oxBiESDH-PKsvvYmTbNlXaRdiycj721OtPdXpFxt6o0_qzbWmfZ71_ildX52zMkFj4eq6odzakm3xta-qf211UZV_isVRvkflWq7_V1z412Vqmpocspj7-tp8Zm9BKv352U2WwUauWgDjinyAoF0HGkKBVBSInKKOGrEOKQcE8oZxzIWwFCrnOU8yqF7AVJIUhx7y4G3sGor987slDtKq4z8a1i3kcq1RlckVZEL4KRD3fGnmguIBBdaoS41jyHpuO4Hrr2zPwdqWrm1B1d350tkcZQAsrRXxGFLO9s0jsp_VWCy90EOPsjeB3nyoUPdDShDRGcIHjFggL8sMIHl</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Obaida, Mohammed Hussein</creator><creator>Elkaffas, Saleh Mesbah</creator><creator>Guirguis, Shawkat Kamal</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | Algorithms Blogs Bullying Convolutional neural networks Cyberbullying Datasets Deep learning Digital media Hate speech Long short term memory LSTM Machine learning Social networking (online) Social networks Support vector machines Young adults |
| title | Deep Learning Algorithms for Cyber-Bulling Detection in Social Media Platforms |
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