Cyberbullying Detection On Social Media Using Machine Learning

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

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

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.

Published Paper   E-Certificate

"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

Volume 8 Issue 3, March-2023

Pages : b821-b825

Paper Reg. ID: IJNRD_188751

Published Paper Id: IJNRD2303191

Downloads: 000118846

Research Area: Engineering

Country: Visakhapatnam, Andhra pradesh, India

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

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

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

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition