Abstract: Governments may have the capacity to flood social media with fake news, but little is known about the use of flooding by ordinary voters. In this work, we identify 2107 registered US voters that account for 80% of the fake news shared on Twitter during the 2020 US presidential election by an entire panel of 664,391 voters. We found that supersharers were important members of the network, reaching a sizable 5.2% of registered voters on the platform. Supersharers had a significant overrepresentation of women, older adults, and registered Republicans. Supersharers' massive volume did not seem automated but was rather generated through manual and persistent retweeting. These findings highlight a vulnerability of social media for democracy, where a small group of people distort the political reality for many.
Nir Grinberg is an Assistant Professor at the Department of Software and Information Systems Engineering at Ben-Gurion University, Israel. His research investigates social behavior in large-scale, online information systems. He studies areas where information systems are suboptimal for people -- for example, by not meeting people's needs, goals or expectations -- and proposes new computational measures to bridge the gaps. For example, he studied the scale and scope of fake news on social media and develops methods for limiting its spread, audits large-scale algorithmic systems such as Google Search and Gmail to reduce bias and inequality, and examines online user engagement with news in order to promote better measures for quantifying it. He collaborated on research projects with top industry partners such as Facebook, Yahoo! Labs, Chartbeat, SocialFlow, and Bloomberg L.P. He holds a Ph.D. in Computer Science from Cornell University, a M.Sc. in Computer Science from Rutgers University, and a double major B.Sc. in Physics and Computer Science from Tel Aviv University.
