manideep2510/siamese-BERT-fake-news-detection-LIAR
Triple Branch BERT Siamese Network for fake news classification on LIAR-PLUS dataset in PyTorch
This project helps fact-checkers and news analysts by automatically classifying news statements as fake or real, or into one of six veracity categories (e.g., Pants on Fire, True). It takes news statements, justifications, and related metadata as input and outputs a classification of the statement's authenticity. This tool would be used by journalists, media researchers, or content moderators who need to quickly assess the truthfulness of information.
152 stars. No commits in the last 6 months.
Use this if you need to classify news statements as fake/real or into more granular categories, leveraging both the statement itself and its supporting context like justifications and speaker metadata.
Not ideal if you need to perform real-time, high-volume fake news detection on streaming data without significant computational resources, or if you primarily work with image or video content.
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48
Language
Python
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Last pushed
Sep 13, 2022
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