As journalists and professional fact-checkers struggle to keep up with the deluge of misinformation online, fact-checking sites that rely on loosely coordinated contributions from volunteers, such as Wikipedia, can help fill the gaps, Cornell research finds.
In a new study, Andy Zhao, a doctoral candidate in information science based at Cornell Tech, compared professional fact-checking articles to posts on Cofacts, a community-sourced fact-checking platform in Taiwan. He found that the crowdsourced site often responded to queries more rapidly than professionals and handled a different range of issues across platforms.
“Fact-checking is a core component of being able to use our information ecosystem in a way that supports trustworthy information,” said senior author Mor Naaman, professor of information science at the Jacobs Technion-Cornell Institute at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science. “Places of knowledge production, like Wikipedia and Cofacts, have proved so far to be the most robust to misinformation campaigns.”
The study, “Insights from a Comparative Study on the Variety, Velocity, Veracity, and Viability of Crowdsourced and Professional Fact-Checking Services,” published Sept. 21 in the Journal of Online Trust and Safety.
The researchers focused on Cofacts because it is a crowdsourced fact-checking model that had not been well-studied. The Taiwanese government, civil organizations and the tech community established Cofacts in 2017 to address the challenges of both malicious and innocent misinformation – partially in response to efforts from the Chinese government to use disinformation to create a more pro-China public opinion in Taiwan. Much like Wikipedia, anyone on Cofacts can be an editor and post answers, submit questions and up or downvote responses. Cofacts also has a bot that fact-checks claims in a popular messaging app.
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