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NewsGuesser: Using Curiosity to Reduce Selective Exposure

Published: 26 April 2024 Publication History

Abstract

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.

Supplemental Material

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Supplemental material includes the participants' demographics, the full interview protocol and the NewsGuesser interface code.

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  1. NewsGuesser: Using Curiosity to Reduce Selective Exposure

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    cover image Proceedings of the ACM on Human-Computer Interaction
    Proceedings of the ACM on Human-Computer Interaction  Volume 8, Issue CSCW1
    CSCW
    April 2024
    6294 pages
    EISSN:2573-0142
    DOI:10.1145/3661497
    Issue’s Table of Contents
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 26 April 2024
    Published in PACMHCI Volume 8, Issue CSCW1

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    1. filter bubble
    2. gamification
    3. selective exposure

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