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Media Bias and Reputation

The main types of social networking services are those which contain category places (such as former school-year or classmates), means to connect with friends (usually with self-description pages) and a recommendation system linked to trust. Popular methods now combine many of these, with Facebook and Twitter widely used worldwide; MySpace and LinkedIn being the most widely used in North America; [1] Nexopia (mostly in Canada); [2] Bebo, [3] Hi5, Hyves (mostly in The Netherlands), StudiVZ (mostly in Germany), iWiW (mostly in Hungary), Tuenti (mostly in Spain), Nasza-Klasa (mostly in Poland), Decayenne, Tagged, XING, [4] Badoo[5] and Skyrock in parts of Europe; [6] Orkut. | Media Bias and Reputation Matthew Gentzkow University of Chicago Jesse M. Shapiro University of Chicago and National Bureau of Economic Research A Bayesian consumer who is uncertain about the quality of an information source will infer that the source is of higher quality when its reports conform to the consumer s prior expectations. We use this fact to build a model of media bias in which firms slant their reports toward the prior beliefs of their customers in order to build a reputation for quality. Bias emerges in our model even though it can make all market participants worse off. The model predicts that bias will be less severe when consumers receive independent evidence on the true state of the world and that competition between independently owned news outlets can reduce bias. We present a variety of empirical evidence consistent with these predictions. We are extremely grateful to an anonymous referee for thorough and insightful comments on an earlier draft of this paper. We also thank Alberto Alesina Attila Ambrus Nigel Ashford Chris Avery Heski Bar-Isaac Gary Becker Tyler Cowen Jonathan Feinstein Jeremy Fox Drew Fudenberg Ed Glaeser Jerry Green James Heckman Tom Hubbard Steve Levitt Larry Katz Kevin M. Murphy Roger Myerson Canice Prendergast Matthew Rabin Andrei Shleifer Lars Stole Richard Thaler Richard Zeckhauser and seminar participants at Harvard University the University of Chicago the Institute for Humane Studies and the University of British Columbia for helpful comments. We thank Christopher Avery Judith Chevalier Matthew Hale Martin Kaplan Bryan Boulier and H. O. Stekler for generously providing access to their data. Karen Bernhardt Fuhito Kojima Jennifer Paniza and Tina Yang provided excellent research assistance. Gentzkow acknowledges financial assistance from the Social Science Research Council and the Centel Foundation Robert P. Reuss Faculty Research Fund. Shapiro acknowledges financial assistance from the Institute for Humane Studies the .