Paper Title

Cyberbullying Detection On Social Media Using Machine Learning

Article Identifiers

Registration ID: IJNRD_188751

Published ID: IJNRD2303191

DOI: Click Here to Get

Authors

Tushara Kodi , M. Sion Kumari , Sirisha Devada , Sindhu Sravya Mangalapalli , Rayapureddy Sivani, Preethi Sandilya Kakarla

Keywords

Cyberbullying, Machine learning, Multinomial Naïve Bayes, Natural Language Processing (NLP)

Abstract

Cyberbullying is a pervasive problem in the digital age that can lead to serious mental and physical harm for its victims. This is a very important and timely research topic, given the increasing prevalence of online abuse and bullying on social media. The use of natural language processing and machine learning to detect abusive messages could be an effective solution to mitigate the negative impact of online harassment. By developing a reliable and accurate technique to detect bullying text, we can potentially prevent or intervene in cases of cyberbullying before they escalate into more serious consequences. This paper proposes an approach for detecting cyberbullying on social media using the naive Bayes algorithm. The proposed method involves the use of natural language processing techniques to preprocess and extract relevant features from textual data, such as social media comments. These features are then used to train a multinomial naive Bayes classifier to classify comments as either cyber bullying or non-cyberbullying. Overall, this research has the potential to make a significant positive impact on society by addressing a critical issue in the digital age.

How To Cite

"Cyberbullying Detection On Social Media Using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.b821-b825, March-2023, Available :https://ijnrd.org/papers/IJNRD2303191.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : b821-b825

Other Publication Details

Paper Reg. ID: IJNRD_188751

Published Paper Id: IJNRD2303191

Downloads: 000121233

Research Area: Engineering

Country: Visakhapatnam, Andhra pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303191.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303191

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

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Call For Paper

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (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) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

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

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

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

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area