How well do current information systems serve us as individuals and as a society? The same systems celebrated for promoting free speech and equality only a decade ago, are now deemed a threat for democracy and a vector for polarization. Yet, much of this heated debate is neither grounded in empirical evidence nor constructive for building better systems for people.
In this talk, I present a computational approach for studying individuals' engagement with fake and real news online. First, I present my work quantifying the scale and scope of fake news on Twitter among voters in the 2016 U.S. presidential election. I describe three methodological innovations that enabled reliable and comprehensive measurement of exposure to and sharing of fake news by U.S. voters on Twitter. I report on the concentration of fake news among voters, the demographic and behavioral characteristics associated with elevated levels of engagement with fake news, and the overall placement of fake news within the broader political news ecosystem. In the second part of the talk, I present methods for news publishers to better quantify readers' engagement with news articles. I show that post-click engagement is accurately described by just six prototypical modes that persist across different publishers and browsing devices. I also show that a novel, text-based measure I developed captures unique information about reading not available otherwise. Finally, I conclude by discussing policy implications for combating fake news and for better evaluating success of real news in the digital age.
Nir Grinberg is a postdoctoral research associate at Northeastern University's Network Science Institute, and research fellow at Harvard University's Institute for Quantitative Social Science. His research investigates areas where existing large-scale 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 Twitter among voters during an election, examined the effect of Facebook likes and comments on people's behavior and attitude, and proposed new measures to quantify engagement with online news. 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.