Factchecking Matters: The Value of Crowdsourcing for Enhanced Accuracy Judgments

Awarded Scholars:
Yu Ding , Columbia University
Project Date:
Jun 2020
Award Amount:

This research project proposes a method to leverage the input of the general population (crowdsourcing), algorithms (supervised learning), and experts (third-party checkers) to detect false information on news media. The principal investigator proposes the use of similarity judgments to facilitate unbiased responses that can be used to predict untrustworthy arguments.


RSF: The Russell Sage Foundation Journal of the Social Sciences is a peer-reviewed, open-access journal of original empirical research articles by both established and emerging scholars.


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