Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
Cyberbullying may be a genuine issue that influences numerous individuals online, particularly on social media stages. Cyberbullying can happen totally different dialects, and it is vital to identify and avoid it in a multilingual setting. In this paper, we propose a Multilingual Cyberbullying Detection System (MCDS) that can recognize cyberbullying in five languages: English, Hindi (Hindi and Hindi-English code-mixed), Marathi, Bengali and Tamil. We utilize a combination of Natural Language Processing and Machine Learning methods to classify content messages as cyberbullying or not. We evaluate our system on several datasets and achieve high accuracy and F1-score and Recall. Our System can be amplified to other languages and domains, and can help to protect clients from online harassment and cyberbullying or abuse. The results of our experiments have shown an accuracy up-to 95% and F1-score up-to 94%.
Keywords:
Cyberbullying, Machine Learning, Multilingual Cyberbullying Detection for Indian languages.
Cite Article:
"Multilingual Cyber-Bullying Detection System", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 11, page no.647 - 652, November-2023, Available :http://www.ijrti.org/papers/IJRTI2311085.pdf
Downloads:
000205291
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator