ekagra-ranjan/fake-news-detection-LIAR-pytorch
Fake News Detection by Learning Convolution Filters through Contextualized Attention
This project helps identify the truthfulness of short statements by analyzing the statement itself along with crucial background details like the speaker, their political party, and the statement's context. You provide a statement and its related metadata, and it outputs a classification indicating how truthful the statement likely is, from 'pants-fire' to 'true'. This tool is for fact-checkers, journalists, or content moderators who need to assess the veracity of public claims.
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Use this if you need an automated way to classify the truthfulness of short claims, especially when you have supplementary information about the claim's origin and speaker.
Not ideal if you need to analyze very long articles or complex narratives, or if you don't have access to detailed contextual information for each statement.
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Python
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Sep 26, 2021
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