Breaking Echo Chambers with Personalized News

Abstract

When a news platform such as Google News or Apple News selects personalized news for its user, will it select news that conforms to its user's bias, thus creating an “echo chamber”? To answer this question, this paper studies a game between a click-maximizing platform and a rational user who tries to learn the true state of the world. We derived the necessary and sufficient conditions for the user to exhibit a preference for headlines that contradict her prior bias, which induces the platform to recommend prior-contradicting headlines. Many classes of distributions, including the Normal distribution, satisfy these conditions. This result stands in contrast with theories of media bias in the literature and is consistent with recent empirical findings.

Keywords: media bias, personalized news, echo chambers, news aggregator, platform

JEL Classification: C72, D83, L82