Programme

BSc (Hons) in Computing in IT

Subject

Computer Science

Abstract

This project focuses on applying Machine Learning (ML) techniques to detect hate speech and offensive language on Twitter, addressing ethical concerns like cyberbullying and fostering a safer online environment. The topic is chosen for its societal significance and business relevance, as hostile online behaviour negatively impacts user experiences and platform credibility.

To achieve this, the study implements four distinct ML models to develop an automated system capable of identifying and categorising content as offensive, non-offensive, or neutral. The system aims to contribute to mitigating harmful interactions on social media and improving user safety by effectively classifying potentially problematic content.

The project's approach underlines the importance of integrating technological solutions to address ethical challenges while aligning with business interests in creating more inclusive digital spaces.

Date of Award

2024

Full Publication Date

2024

Access Rights

open access

Document Type

Undergraduate Project

Resource Type

bachelor thesis

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