Automatic Detection of Cyberbullying using Machine Learning

Cyberbullying is one of the most recent evils of social media. With a boom in the usage of social media, the freedom of expression is being exploited. The program presents a multi-group chat application developed using Python sockets and a Tkinter-based graphical user interface (GUI). The application allows users to create and join chat rooms, send text messages, and share files within rooms. Additionally, an AI-based message filtering system is integrated to detect and hide messages containing bullying content using a pre-trained Linear SVC model. The system enhances real-time communication while ensuring a safe chat environment by preventing offensive or harmful conversations.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-09
DOI
https://doi.org/10.22214/ijraset.2025.68277
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Automatic Detection of Cyberbullying using Machine Learning

P. Patil
International Journal for Research in Applied Science and Engineering Technology
Hate Speech and Cyberbullying Detection
article

Automatic Detection of Cyberbullying using Machine Learning

P. Patil
article en

Abstract

Cyberbullying is one of the most recent evils of social media. With a boom in the usage of social media, the freedom of expression is being exploited. The program presents a multi-group chat application developed using Python sockets and a Tkinter-based graphical user interface (GUI). The application allows users to create and join chat rooms, send text messages, and share files within rooms. Additionally, an AI-based message filtering system is integrated to detect and hide messages containing bullying content using a pre-trained Linear SVC model. The system enhances real-time communication while ensuring a safe chat environment by preventing offensive or harmful conversations.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 97%
Hate Speech and Cyberbullying Detection
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