Predicting the Influence of Fake and Real News Spreaders (Student Abstract)
Keywords:Misinformation, Fake News Spreaders, User Influence Prediction
AbstractWe 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.
How to Cite
Zhang, A., Brookhouse, A., Hammer, D., Spezzano, F., & Babinkostova, L. (2022). Predicting the Influence of Fake and Real News Spreaders (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13107-13108. https://doi.org/10.1609/aaai.v36i11.21690
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