Paper Title
MACHINE LEARNING BASED AUTOMATIC HATE SPEECH RECOGNITION SYSTEM
Article Identifiers
Authors
Sayyad Fardheen Ahmad , Dr.G.Rosline Nesa Kumari , Seelam Govardhan Reddy , Shaik.Basheer , Shaik Yasin
Keywords
cyberbullying, machine learning, convolutional neural network, deep learning, feature extraction, text classification.
Abstract
Cyberbullying is a serious trouble on online that impacts each old and young. This results in incidents like demise and despair. Content curation is increasing the need for social media structures. The following study uses facts on varieties of cyberbullying: hate tweets on Twitter and personal assaults on Wikipedia boards. Three function extraction strategies and four classifiers were used to decide the best method. For tweet records, the model achieves over 90% accuracy and for Wikipedia information, over 80% accuracy.
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How To Cite (APA)
Sayyad Fardheen Ahmad, Dr.G.Rosline Nesa Kumari, Seelam Govardhan Reddy, Shaik.Basheer, & Shaik Yasin (April-2024). MACHINE LEARNING BASED AUTOMATIC HATE SPEECH RECOGNITION SYSTEM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), c416-c420. https://ijnrd.org/papers/IJNRD2404280.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : c416-c420
Other Publication Details
Paper Reg. ID: IJNRD_217859
Published Paper Id: IJNRD2404280
Downloads: 000121980
Research Area: Engineering
Country: Chennai, Tamil Nadu, Tamil Nadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404280.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404280
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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