Lunch Seminar Series | Can We Crowdsource Fact Checking? Initial Findings from a New NYU-Stanford Collaboration

Date and Time

February 11, 2020 1:00 PM - 2:15 PM

Availability

RSVP

Open to Stanford faculty, students, staff, and visiting scholars.

RSVP required by 5PM February 11.

Location

Reuben W. Hills Conference Room
Encina Hall, Second Floor, East Wing, E207
616 Jane Stanford Way, Stanford, CA 94305

The research on misinformation generally and fake news specifically is vast, as is coverage in media outlets. Two questions run throughout both the academic and public discourse: what explains the spread of fake news online, and what can be done about it? While there is substantial literature on who is likely to be exposed to and share fake news, these behaviors might not signal belief or effect. Conversely, there is far less work on who is able to differentiate between true and false stories and, as a result, who is most likely to believe fake news (or, conversely, not believe true news), a question that speaks directly to Facebook’s recent “community review” approach to combating the spread of fake news on its platform.

In his talk, Professor Tucker will report on initial findings from a new collaborative project between NYU’s Center for Social Media and Politics and Stanford’s Program on Democracy and the Internet designed to fill these gaps in the scholarly literature and inform the types of policy decisions being made by Facebook. The project has enlisted both professional fact checkers and random “crowds” of close to 100 people to fact check five “fresh” articles (that have appeared in the past 24 hours) per day, four days a week, for eights week using an innovative transparent and replicable algorithm for selecting the articles for fact checking. He will report on initial observations regarding (a) individual determinants of fact checking proficiency; (b) the viability using the “wisdom of the crowds” for fact checking, including examining the tradeoffs between crafting a more accurate crowd vs. a more representative crowd and (c) results from experiments designed to assess potential policy interventions to improve crowdsourcing accuracy.

About the Speaker:

Joshua TuckerJoshua A. Tucker is Professor of Politics, affiliated Professor of Russian and Slavic Studies, and affiliated Professor of Data Science at New York University. He is the Director of NYU’s Jordan Center for Advanced Study of Russia, a co-Director of the NYU Social Media and Political Participation (SMaPP) laboratory, a co-Director of the new NYU Center for Social Media and Politics, and a co-author/editor of the award-winning politics and policy blog The Monkey Cage at The Washington Post. He serves on the advisory boards of the American National Election Study, the Comparative Study of Electoral Systems, and numerous academic journals. Originally a scholar of post-communist politics, he has more recently studied social media and politics. His research in this area has included studies on the effects of network diversity on tolerance, partisan echo chambers, online hate speech, the effects of exposure to social media on political knowledge, online networks and protest, disinformation and fake news, how authoritarian regimes respond to online opposition, and Russian bots and trolls. His research has been funded by over $8 million in grants in the past three years, including a 2019 Knight Foundation “Research on the Future of an Informed Society” grant. His most recent book is the co-authored Communism’s Shadow: Historical Legacies and Contemporary Political Attitudes (Princeton University Press, 2017), and he is the co-editor of the forthcoming edited volume Social Media and Democracy (Cambridge University Press, 2020).