HomeProjectsArtificial Intelligence & Machine LearningReal-Time Misinformation & Fake News Detector with Explainable BERT
Artificial Intelligence & Machine LearningB.Tech • BCA • MCAComplexity: IntermediateIEEE Verified

Real-Time Misinformation & Fake News Detector with Explainable BERT

Deep bidirectional transformer NLP model evaluating news credibility, emotional sensationalism bias, and source provenance with Chrome Extension integration.

Core Stack:PythonHugging Face TransformersRoBERTaFastAPIReactChrome Extension Manifest v3
4.7(25 Academic Reviews)
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₹4,399₹6,599Save 35%
Full Source Code & Database SQL
60-Page IEEE Project Report (.docx & .pdf)
25-Slide Seminar Presentation Deck (.pptx)
50+ Viva Voce Questions & Answers Guide
Real-Time Misinformation & Fake News Detector with Explainable BERT preview 1
Verified System Artifact #1

Detailed Project Overview

A full-stack NLP system built on RoBERTa and DistilBERT. Extracts linguistic cues, lexical clickbait markers, and cross-references claim statements against verified fact-checking APIs. Features a browser extension that evaluates news articles in real-time.

Academic Problem Statement

Viral misinformation on social channels distorts public health advice and electoral integrity. Everyday readers need an instant browser-level credibility score.

Proposed Methodology & Flow

Fine-tuned RoBERTa transformer on WELFake & ISOT benchmarks; LIME / SHAP explainability layer highlights deceptive sentence fragments in red.

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