View Proposal

Proposer
Abhishek Ghai
Title
Automated Fake News Detection System
Goal
Description
Students select or source a labeled dataset of news content and design a full text classification pipeline, from cleaning and preparing raw text through to a trained model capable of distinguishing credible from misleading content. The project should involve comparing at least two different modeling approaches and evaluating them using metrics appropriate for imbalanced data, not accuracy alone. The system should be presented through a simple interface where a user can input a piece of text and receive a credibility assessment, ideally with some indication of what influenced that judgment.
Resources
Background
Url
Difficulty Level
Easy
Ethical Approval
None
Number Of Students
1
Supervisor
Abhishek Ghai
Keywords
natural language processing, text classification, misinformation detection, machine learning, sentiment analysis, feature extraction, model evaluation
Degrees
Bachelor of Science in Computational Sciences and Software Engineering
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