NewsGuesser: Using Curiosity to Reduce Selective Exposure

• Published in: Proceedings of the ACM on human-computer interaction 2024-04, Vol.8 (CSCW1), p.1-22, Article 99
• Main Authors: Sun, Lu, Zhang, Hengyuan, Liu, Enze, Liu, Mingyang, Vaccaro, Kristen
• Format: Article
• Language: English
• Subjects: Empirical studies in HCI; Human computer interaction (HCI); Human-centered computing
• ISSN: 2573-0142; 2573-0142
• DOI: 10.1145/3637376

Selective exposure has long been a concern of HCI researchers as it can lead to ideological polarization and distrust in society. Efforts have tried to reduce selective exposure online by serving diversified news content, but their effectiveness has been limited by users' lack of motivation to engage with the diverse content offered. To address this, we design the NewsGuesser system, which leverages the insight that curiosity can prompt motivation and engagement, by asking readers to guess the source of their news. In interviews with 40 participants, balanced for partisan affiliation, we use NewsGuesser as a probe tool to explore how guessing affects their perceptions of selective exposure. Participants struggled with the guessing game, which revealed a misalignment between users' expectations of different news sources and reality. Faced with the visualizations of the (often inaccurate) guessing results, participants were able to reflect on their own biases and selective exposure. In a number of cases, the guessing process changed participants' impressions of news organizations and some expressed an interest in engaging with more diverse news sources. While many also found the guessing game frustrating, the system and interview results suggest a number of new directions for designing social media and news media platforms.