This framework utilizes the BERT (Bidirectional Encoder Representations from Transformers) model to analyze the semantic and sentimental nuances of news articles. By examining the relationship between headline sentiment and body content, the system identifies clickbait and emotionally charged misinformation. The project involves training on large-scale datasets of verified and fabricated news to learn complex linguistic markers of deception. The resulting system provides a credibility score for textual content, serving as a critical tool for digital publishers and social media platforms to maintain information integrity.
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AI / ML Projects, Artificial Intelligence Projects, Natural Language Processing
Sentiment Analysis Framework for Fake News Detection Using BERT and Transformers
Original price was: ₹6,999.00.₹3,999.00Current price is: ₹3,999.00. inc GSTs*
The viral spread of misinformation on social media often relies on manipulative emotional cues and polarized sentiment. Current metadata-based filters are insufficient, requiring advanced linguistic analysis to identify the subtle emotional discrepancies and stylistic patterns characteristic of synthetically generated or deceptive news content.

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