Paper Title

SOCIAL MEDIA OFFENSIVE CONVERSATION DETECTION USING MACHINE LEARNING

Article Identifiers

Registration ID: IJNRD_210015

Published ID: IJNRD2311388

DOI: Click Here to Get

Authors

Dhineshkumar T , Preethika S , Prasath M , Sasikala K , Sasikala B

Keywords

cyberbullying, abusive language detection, convolutional neural network (CNN), comparative analysis, offensive language, Friendly Chat application.

Abstract

The proliferation of social media has led to a surge in daily comments, accompanied by a troubling increase in abusive language. This study addresses the urgent issue of cyberbullying through abusive online comments, targeting individuals and groups based on various criteria. Automatic detection of abusive language is crucial for mitigating this problem. Experimental results highlight the superiority of the convolutional neural network (CNN), achieving impressive accuracy rates of 96.2%, 91.4%, and an undisclosed mixed-language dataset. The research emphasizes the effectiveness of one-layer architectures in deep learning models over two-layer architectures. Comparative analysis affirms the significant superiority of deep learning models in detecting and classifying abusive language. In a related context, an application called "Friendly Chat" is introduced to track offensive language in social media chats, fostering respectful interactions. Utilizing a "toxic comment" dataset rated by human critics, the application classifies posts into categories like abuse and hatred. Employing techniques such as Naïve Bayes, LSTM, and Binary relevance, the application detects abusive users in real-time, contributing to a safer online environment.

How To Cite (APA)

Dhineshkumar T, Preethika S, Prasath M, Sasikala K, & Sasikala B (November-2023). SOCIAL MEDIA OFFENSIVE CONVERSATION DETECTION USING MACHINE LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(11), d799-d804. https://ijnrd.org/papers/IJNRD2311388.pdf

Issue

Volume 8 Issue 11, November-2023

Pages : d799-d804

Other Publication Details

Paper Reg. ID: IJNRD_210015

Published Paper Id: IJNRD2311388

Downloads: 000121984

Research Area: Information Technology 

Country: Dharmapuri, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2311388.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2311388

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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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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

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