HATE SPEECH DETECTION

  • Unique Paper ID: 149275
  • Volume: 6
  • Issue: 11
  • PageNo: 506-509
  • Abstract:
  • As online content continues to grow, so does the spread of hate speech. We identify and examine challenges faced by online automatic approaches for hate speech detection in text. The increasing propagation on social media and the urgent need for effective countermeasures have drawn significant investment from governments, companies, and researchers. Machine Learning and predictive analytics now help companies to focus on important areas, anticipating problems before they happen, reducing costs, and increasing revenue.

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{149275,
        author = {Sonam Singh and Shivani Shinde and Subodh Nikumbh and Prof. Dhiraj Amin},
        title = {HATE SPEECH DETECTION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {11},
        pages = {506-509},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=149275},
        abstract = {As online content continues to grow, so does the spread of hate speech. We identify and examine challenges faced by online automatic approaches for hate speech detection in text. The increasing propagation on social media and the urgent need for effective countermeasures have drawn significant investment from governments, companies, and researchers. Machine Learning and predictive analytics now help companies to focus on important areas, anticipating problems before they happen, reducing costs, and increasing revenue.},
        keywords = {Hate Speech, Classification, NLP, SVM, Naive Bayes, Bag of Words (BOW).
},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 6
  • Issue: 11
  • PageNo: 506-509

HATE SPEECH DETECTION

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