Description:

Wednesdays@NICO Seminar | 12:00-1:00 PM, February 11, 2015 | Chambers Hall

Marcus Mobius, Microsoft Research

Abstract
This paper analyzes how the audience for internet news varies with the source of the referral, comparing the audience when users navigate directly to news outlets to that when users are referred by social media. On average, the audience referred by social media reads different types of articles, for example, articles with more emotional content and articles that show an individual’s perspective. We find that much of the difference in audience can be explained by the fact that different types of users use social media as a news source with different propensities, and further different topics are consumed on social media. We also study the problem from the user perspective showing that a given user is more likely to consume news that aligns with their political preferences (as revealed through their past browsing) through social media. That is, social media seems to exacerbate polarization in information consumption. The paper develops a novel methodology for categorizing news at a large scale, combining text mining and crowd sourcing techniques. With these methods we are able to provide evidence about a variety of qualitative features of news consumption at a large scale, including subtle factors such as whether an article is of a type that would typically be shared to impress one’s social media friends (joint with Susan Athey and Jeno Pal).

Bio
My main research agenda deals with the economics of social networks. On the theory side, I build models of learning, coordination and cooperation within social networks. I am particularly interested in how social networks can generate trust. In joint work with my coauthors Adam Szeidl, Tanya Rosenblat, Attila Ambrus and Dean Karlan we developed the social collateral approach to social capital which provides a tractable framework to think about repeated games in social networks. We created a dedicated website which lists our relevant research papers as well as software: The Social Collateral Approach to Social Capital.

On the empirical side, I use a combination of lab and field experiments with real social networks to estimate these models. In a second line of research I have explored the impact of non-resume variables like confidence and physical attractiveness in the labor market. Recently, I have also become interested in using browsing data to analyze the economics of online news consumption.