The effects of crowd worker biases in fact-checking tasks

2022-06-20

Presented at the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency (June 2022), Seoul, South Korea

Additional Metadata
Keywords	Crowdsourcing, Bias, Misinformation, Explainability, Truthfulness
Persistent URL	doi.org/10.1145/3531146.3534629
Conference	FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency
Organisation	Human-Centered Data Analytics
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Draws, T., La Barbera, D., Soprano, M., Roitero, K., Ceolin, D., Checco, A., & Mizzaro, S. (2022). The effects of crowd worker biases in fact-checking tasks. In FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency (pp. 2114–2124). doi:10.1145/3531146.3534629

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