Understanding How News Recommender Systems Influence Selective Exposure

Abstract

News recommender systems (NRSs) offer benefits in the realm of information consumption and person- alized news delivery. Yet, some critics argue that overly personalized news recommendations can pose a threat to democracy as these systems can potentially increase the occurrence of selective exposure, where individuals seek out political news that confirms their opinions at the expense of political news that contradicts their opinions. However, the conditions under which NRSs amplify or reduce selective exposure and the extent to which this happens are still poorly understood. Therefore, we ask: To what extent can NRSs influence the selective exposure behavior of news users? We present a preregistered online experiment to empirically test the impact of structural factors on selective exposure. We track user behavior on a news website equipped with two different versions of custom-made NRSs that are specifically designed to present news articles in such a way that we assume to nudge users towards increased or decreased selective exposure to like-minded or cross-cutting news. The findings indicate that the positioning and size of news articles have a notable impact on participants’ behavior. Specifically, larger articles placed at the top tend to be more attractive for selection when they align with participants’ attitudes. On the other hand, smaller articles placed at the bottom are less likely to capture participants’ attention if they are attitude-consistent. The findings provide evidence that it may be possible to program NRSs to reduce selective exposure by promoting certain factors in the design of NRSs.