INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The rise of hate speech in online platforms poses a significant societal concern, necessitating effective detection and mitigation strategies. This research presents a robust approach to detect hate speech using machine learning algorithms. The study leverages the Glove Twitter dataset and extracts tweets directly from Twitter using the Twitter API. Three distinct machine learning algorithms - Random Forest, Logistic Regression, and Support Vector Machine (SVM) - are employed to train models for hate speech detection. The obtained accuracies for Random Forest, Logistic Regression, and SVM are 98.16%, 87.77%, and 98.54%, with F1 scores recorded at 98.1318%, 88.0759%, and 98.5313% respectively. The results demonstrated the effectiveness of the Support Vector Machine in hate speech detection and highlight the importance of leveraging machine learning for fostering a safer online environment.
Keywords:
Hate speech, Sentiment analysis, Social media, Machine learning
Cite Article:
"An Approach to Detection of Sexism and Racism in Hate Text-Speech Using Machine Learning Algorithms", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 10, page no.c550-c557, October-2023, Available :http://www.ijnrd.org/papers/IJNRD2310258.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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