Papers with HEARD

    1 papers
    Early Rumor Detection Using Neural Hawkes Process with a New Benchmark Dataset (2022.naacl-main)

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    Challenge: rumor detection models have been designed with oversimplifcation and evaluated inappropriately on a few datasets where the actual early-stage information is largely missing.
    Approach: They propose a new Benchmark dataset for EArly Rumor Detection based on claims from fact-checking websites and a novel model based upon neural Hawkes process for EARD.
    Outcome: The proposed model can guide a generic rumor detection model to make timely, accurate and stable predictions.

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