Social Media Forensics: An Machine Learning Approach for Cyberbullying Tweet Recognition

Social Media Forensics: An Machine Learning Approach for Cyberbullying Tweet Recognition

Authors- Dhaneshwaran S, Assistant Professor H.Jayamangala

Abstract-Cyberbullying is becoming a more serious problem on social media sites, and victims frequently suffer from serious psychological effects. This project showcases a Cyberbullying Tweet Recognition System that was created with Streamlit as an interactive web application. The system’s objective is to automatically categorize tweets into six groups: Religion, Not Cyberbullying, Ethnicity, Gender, and Age. There are two main modes that the tool supports: Single Tweet Analysis, which allows users to enter a single tweet and get predictions right away.Bulk Analysis, which lets users submit datasets for the classification of tweets on a big scale.To make system administration easier, an admin interface is included. It allows users to upload new datasets, Developing and maintaining classification models, looking at performance indicators like accuracy scores and confusion matrices.

DOI: /10.61463/ijset.vol.13.issue3.103