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Why Do You Need This?: Selective Disclosure of Data Among Citizen Scientists

Published: 02 May 2019 Publication History

Abstract

Recent scandals involving data from participatory research have contributed to broader public concern about online privacy. Such concerns might make people more reluctant to participate in research that asks them to volunteer personal data, compromising many researchers' data collection. We tested several motivational messages that encouraged participation in a citizen science project. We measured people's willingness to disclose personal information. While participants were less likely to share sensitive data than neutral data, disclosure behaviour was not affected by attitudes to privacy. Importantly, we found that citizen scientists who were exposed to a motivational message that emphasised 'learning' were more likely to share sensitive information than those presented with other types of motivational cues. Our results suggest that priming individuals with motivational messages can increase their willingness to contribute personal data to a project, even if the request pertains to sensitive information.

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  • (2024)Exploring the Future of Informed Consent: Applying a Service Design ApproachProceedings of the ACM on Human-Computer Interaction10.1145/36373308:CSCW1(1-31)Online publication date: 26-Apr-2024
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  • (2023)What is Sensitive About (Sensitive) Data? Characterizing Sensitivity and Intimacy with Google Assistant UsersProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581164(1-16)Online publication date: 19-Apr-2023
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    cover image ACM Conferences
    CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
    May 2019
    9077 pages
    ISBN:9781450359702
    DOI:10.1145/3290605
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    Published: 02 May 2019

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    Author Tags

    1. citizen science
    2. dabblers
    3. disclosure
    4. motivation
    5. privacy

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    CHI '19 Paper Acceptance Rate 703 of 2,958 submissions, 24%;
    Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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    Cited By

    View all
    • (2024)Exploring the Future of Informed Consent: Applying a Service Design ApproachProceedings of the ACM on Human-Computer Interaction10.1145/36373308:CSCW1(1-31)Online publication date: 26-Apr-2024
    • (2024)Communicating the Privacy-Utility Trade-off: Supporting Informed Data Donation with Privacy Decision Interfaces for Differential PrivacyProceedings of the ACM on Human-Computer Interaction10.1145/36373098:CSCW1(1-56)Online publication date: 26-Apr-2024
    • (2023)What is Sensitive About (Sensitive) Data? Characterizing Sensitivity and Intimacy with Google Assistant UsersProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581164(1-16)Online publication date: 19-Apr-2023
    • (2022)Users’ Information Disclosure Behaviors during Interactions with Chatbots: The Effect of Information Disclosure NudgesApplied Sciences10.3390/app12241266012:24(12660)Online publication date: 10-Dec-2022
    • (2021)Privacy Personas for IoT-Based Health Research: A Privacy Calculus ApproachFrontiers in Digital Health10.3389/fdgth.2021.6757543Online publication date: 16-Dec-2021
    • (2021)Public Attitudes to Digital Health Research Repositories: Cross-sectional International SurveyJournal of Medical Internet Research10.2196/3129423:10(e31294)Online publication date: 29-Oct-2021
    • (2020)Futures for Health Research Data Platforms From the Participants’ PerspectivesProceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society10.1145/3419249.3420110(1-14)Online publication date: 25-Oct-2020

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