Cues for you: a comparative test of agenda cueing and attitudes toward algorithmic news in the US and the UK

Abstract Agenda cues, or news heuristics that signal issue importance, are an important determinant of the public’s issue priorities. As these cues shift from editorial recommendations to personalized algorithms, we test the boundary conditions of the agenda cueing hypothesis. We use a comparative online experiment to examine how two different regulatory environments in the US and the UK replicate established cueing effects and provide a formal test of their underlying causal mechanism. Results from the US sample confirm that journalistic agenda cues are effective at cueing issue importance, but algorithmic cues are not. Algorithmic cueing effects do not interact with respondents’ general attitudes toward AI nor their attitudes toward algorithmic news to influence their issue judgments but rather are contingent on one’s ideology and political interest. Implications of journalistic and algorithmically derived agenda cues in different regulatory environments are discussed.