Users of news recommender systems read news recommended by algorithms and can discover useful information unintentionally or serendipitously. The feeling of surprise from this discovery can elicit users to continue reading. Increasing serendipity is believed to be a solution to isolated information bubbles; however, little research has explored its impact on news consumption. The study investigates the interactions between surprise, serendipity, and news consumption. Participants (N = 463) recruited from Amazon MTurk in the United States participated in the online experiment. The findings suggest that serendipitous news discovery directly increases news consumption, with this relationship mediated by the feeling of surprise. Furthermore, users who experience higher serendipitous news discovery indicate more positive attitudes toward news consumption in these systems. The research integrates serendipity into news selection theories and contributes to a more nuanced understanding of how algorithmic systems can enhance user engagement. The results offer key implications for communication scholars and practitioners.
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