Predicting the Influence of Fake and Real News Spreaders (Student Abstract)

Amy Zhang, Aaron Brookhouse, Daniel Hammer, Francesca Spezzano, Liljana Babinkostova

[AAAI-22] Student Abstract and Poster Program - FINALIST

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Poster Session 5 @ Blue 4, Poster Session 12 @ Blue 4, Poster Session 5, Poster Session 12

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Abstract: We study the problem of predicting the influence of a user in spreading fake (or real) news on social media. We propose a new model to address this problem which takes into account both user and tweet characteristics. We show that our model achieves an F1 score of 0.853, resp. 0.931, at predicting the influence of fake, resp. real, news spreaders, and outperforms existing baselines. We also investigate important features at predicting the influence of real vs. fake news spreaders.

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  • Poster Session 5

    Sat, February 26 12:45 AM - 2:30 AM (+00:00)
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  • Poster Session 12

    Mon, February 28 8:45 AM - 10:30 AM (+00:00)
    Blue 4
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