Detection of Cyberbullying on Social Media Using Machine Learning

  • Unique Paper ID: 155140
  • Volume: 8
  • Issue: 12
  • PageNo: 1566-1569
  • Abstract:
  • Cyberbullying is a major problem encountered on the internet that affects teenagers and also adults. It has led to mishappenings like suicide and depression. Regulation of content on Social media platforms has become a growing need. The following study uses data from two different forms of cyberbullying, hate speech tweets from Twitter and comments based on personal attacks from Wikipedia forums to build a model based on the detection of Cyberbullying in text data using Natural Language Processing and Machine learning. Three methods for Feature extraction and four classifiers are studied to outline the best approach. For Tweet data, the model provides accuracies above 90% and for Wikipedia data, it gives accuracies above 80%.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{155140,
        author = {B.PRASANNA KUMAR and Ch Vishnu Vardhan Reddy and Ch Phanendra Reddy and Ch Venkatesh and G.Mahanvith},
        title = {Detection of Cyberbullying on Social Media Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {1566-1569},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155140},
        abstract = {Cyberbullying is a major problem encountered on the internet that affects teenagers and also adults. It has led to mishappenings like suicide and depression. Regulation of content on Social media platforms has become a growing need. The following study uses data from two different forms of cyberbullying, hate speech tweets from Twitter and comments based on personal attacks from Wikipedia forums to build a model based on the detection of Cyberbullying in text data using Natural Language Processing and Machine learning. Three methods for Feature extraction and four classifiers are studied to outline the best approach. For Tweet data, the model provides accuracies above 90% and for Wikipedia data, it gives accuracies above 80%.},
        keywords = {Cyberbullying, Hate speech, Personal attacks, Machine learning, Feature extraction, Twitter, Wikipedia },
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 8
  • Issue: 12
  • PageNo: 1566-1569

Detection of Cyberbullying on Social Media Using Machine Learning

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