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)
The rise of social networking platforms and widespread use of electronic communication have given rise to cyberbullying, a global epidemic with severe consequences. This project addresses the limitations of existing cyberbullying detection methods by leveraging deep learning models. The proposed system aims to overcome bottlenecks related to specific social media platforms, limited topic coverage, and reliance on handcrafted features. The models developed in this study showcase adaptability and transferability across different datasets, as demonstrated through experiments on real- world Twitter data.
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Cite Article:
"A Survey on Cyber Bullying Detection using Machine Learning Models", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 1, page no.320 - 335, January-2024, Available :http://www.ijrti.org/papers/IJRTI2401056.pdf
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000205181
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