From passive to active: How does algorithm awareness affect users’ news seeking behavior on digital platforms

Algorithms are increasingly pervasive in digital platforms, often operating unnoticed by users. Despite this, there is limited understanding of the extent to which users recognize and understand algorithms and how this awareness influences their platform behavior. This study draws on Social Cognitive Theory and Uses & Gratifications Theory to investigate users’ active information behavior, focusing on their cognitive processes in perceiving and interacting with algorithms. Using survey data from 1,158 users of an algorithm-driven news platform, we found that information- and opinion-driven motivations predict active news seeking behavior, while entertainment motivation negatively influences it. Intriguingly, algorithm awareness mediates the relationships between social, opinion, and entertainment motivations and active news seeking, but not for information-motivated users, who seek news actively regardless of their algorithmic understanding. Platform transparency further moderates the relationship between awareness and active news seeking. This study offers both theoretical and practical insights for researchers and practitioners aiming to achieve sustainable human-algorithm interaction.