TruthLens: AI-Powered Fake News and Misinformation Detection Using Multimodal Analysis Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.55041/ijsrem.ncft030
· OA: W4411385920
The spread of misinformation and fake news poses a significant challenge in today’s digital landscape. This research presents TruthLens, an AI-powered framework integrating Nat- ural Language Processing (NLP), Computer Vision (CV), and Fact-Checking APIs to identify and mitigate misinformation. Our system leverages machine learning models for textual analysis, deep learning-based image/video forensics, and web scraping techniques for real-time verification. The credibility scores are evaluated using TF-IDF with LinearSVC, BERT, RoBERTa, CNNs for manipulated media, and Google Fact-Check API, achieving a robust, multi-modal detection pipeline. Index Terms—Misinformation Detection, Fake News, Artificial Intelligence (AI), Natural Language Processing (NLP), Computer Vision (CV), Fact-Checking APIs, Machine Learning, Deep Learning, Media Manipulation Detection, Multi-Modal Detection
