mlsanityData to 14 Oct 2026

Identifying COVID-19 Fake News in Social Media

arXiv 2101.11954 ↗First posted 28 Jan 2021cs.CL cs.AI cs.IRcited by 1

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Abstract (arXiv)

The evolution of social media platforms have empowered everyone to access information easily. Social media users can easily share information with the rest of the world. This may sometimes encourage spread of fake news, which can result in undesirable consequences. In this work, we train models which can identify health news related to COVID-19 pandemic as real or fake. Our models achieve a high F1-score of 98.64%. Our models achieve second place on the leaderboard, tailing the first position with a very narrow margin 0.05% points.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 19 references that are in the map. First posted on arXiv 28 Jan 2021.

Builds on

11 of 19 references.

References · 11

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Citing papers per year: 2021: 1.

1 paper.

  1. 2021Automated Evidence Collection for Fake News Detectioncited by 0