Cross-Cutting exposure, perceived realism, and online political engagement in the age of algorithms

Abstract

Considering the implications of cross-cutting exposure for democratic deliberation in the age of algorithms, this study proposes a conceptual model that delineates the roles of perceived realism and approval of algorithmic curation in the relationship between cross-cutting exposure and online political engagement. Secondary data obtained from the 2018 national survey conducted by the Taiwan Institute for Governance and Communication Research were utilized to test the relationships. The results indicated a negative association between cross cutting exposure and online political engagement. The significant mediation model further showed that exposure to cross-cutting perspectives on social media was negatively associated with online political engagement by way of decreased perceived realism. That association was conditioned by the level of approval of algorithmic curation, which weakened the negative mediating role of perceived realism as it increased. Implications of those results and directions for future research are discussed.