Fourth International Conference on Communication & Media Studies

Abstract

As news organizations increasingly use online, social media platforms to distribute news to consumers, there is an increasing concern that news audiences in these high-choice media environments will only silo themselves in partisan echo chambers. In order to address this issue, previous research has framed this potential issue in terms of two, often competing issues: selective exposure, whether or not news consumers actively choose to only consume news that confirm their pre-existing beliefs, and filter-bubbles, whether news algorithms and recommender systems unknowingly silo audiences into homogenous news environments. This paper suggests that while these approaches are both beneficial in helping us to understand how people seek out and consume news in the digital age, they both only tell half the story. In failing to consider the way in which these two forces interact in guiding contemporary news viewing habits, many of these studies only provide us with a partial understanding of how the majority of news viewing online occurs. In addressing this gap, this paper proposes to bridge these two lines of literature by introducing a model of social media news viewing that centers around the analytic of trust. This paper suggests that trust may be used by future researchers as a way to simultaneously explore the level at which news viewing habits are impacted by selective exposure and algorithmically based social media platforms. Thus, this paper proposes a model that positions trust as a key determinant in both how these factors shape individuals’ news viewing experiences.