Utilizing Machine Learning for Detecting Cyber Bullying in Social Media

Saba Yousha ()
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Saba Yousha: Department of Computer Information & Engineering, Mehran University of Engineering and Technology Jamshoro SINDH, Pakistan

International Journal of Innovations in Science & Technology, 2023, vol. 5, issue 4, 760-772

Abstract: The widespread dominance of the Internet and Electronic Media has made Social Media platforms a primary mode of communication. Unfortunately, these platforms have also become breeding grounds for harmful behavior, notably "Cyber Bullying," which involves using technology to inflict disrespect and harm on others. Despite various efforts by researchers to address this issue, the detection of such behavior remains crucial in combating this menace. This study aims to emphasize an effective approach for detecting cyberbullying on Social Media platforms. The findings indicate that the SVM (Support Vector Machine) classifier outperforms other classifiers in this context.We acquired tweet data from Twitter and used significant machine learning techniques to classify and forecast whether tweets are "offensive" or "non-offensive" and after that, using the Support Vector Machine'sAlgorithm, a machine learning-modelis prepared to detect Cyber Bullying on Social Media Platform.This research provide promising resultsto useML techniques for detection of Cyber Bullying.

Keywords: Cyberbullying; Support Vector Machine (SVM); Machine Learning; Social Media Platforms; Detection (search for similar items in EconPapers)
Date: 2023
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