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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 13, ISSUE 4, APRIL 2024

TOXIC COMMENT CLASSIFICATION SYSTEM USING DEEP LEARNING

Chaitanya Sonawane, Tejaswini Bagale, Preeti Kawade, Swarada Ogale,Prof. Megha C Singru

DOI: 10.17148/IJARCCE.2024.13465

Abstract: Every day, a significant volume of textual content is shared online. Sorting through such vast amounts of textual material to find the relevant and irrelevant information is challenging. One area of natural language processing that enables the examination of textual data is sentiment analysis. Since it examines the words and presents the public’s overall viewpoint, it is regarded as an opinion mining technique [1].Sentiment analysis is a domain with three sub-branches: aspect-based, sentence-based, and document-based [2]. Sentences are used to find opinions in sentence-based sentiment analysis. Sentiment analysis of complicated texts is a challenging task. When conducting sentiment analysis on documents, the entire textual Social media provides a forum for public sharing.their opinions and concepts. The most widely used social media sites are Facebook, Twitter, and YouTube, where usersrespond by leaving comments and like the page. Sentiment analysis is a widely utilised tool for analysis these days.

Keywords: toxic comment,Machine Learning,SVM,NLP.

How to Cite:

[1] Chaitanya Sonawane, Tejaswini Bagale, Preeti Kawade, Swarada Ogale,Prof. Megha C Singru, “TOXIC COMMENT CLASSIFICATION SYSTEM USING DEEP LEARNING,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2024.13465