Algorithm-driven news use and citizens’ political information engagement

Abstract

The diversification of news channels and information platforms has reshaped how citizens are exposed to political information and rumors. This study examines the political implications of diverse forms of news exposure, focusing on three distinct categories: non-algorithmic news, algorithmic news, and messenger-mediated news. Through a survey of 1000 South Korean adults, we analyze how these different types of news exposure are associated with citizens’ political knowledge and beliefs in political rumors. Our findings indicate that these forms of news exposure are differently linked to political knowledge and rumor beliefs, highlighting the various pathways through which news is encountered and processed. We discuss the implications of these findings for misinformation mitigation and draw attention to the need to examine the nature of information exposure with greater granularity.