Shifting Trust: Examining How Trust and Distrust Emerge, Transform, and Collapse in COVID-19 Information Seeking

要旨

During crises like COVID-19, individuals are inundated with conflicting and time-sensitive information that drives a need for rapid assessment of the trustworthiness and reliability of information sources and platforms. This parallels evolutions in information infrastructures, ranging from social media to government data platforms. Distinct from current literature, which presumes a static relationship between the presence or absence of trust and people’s behaviors, our mixed-methods research focuses on situated trust, or trust that is shaped by people's information-seeking and assessment practices through emerging information platforms (e.g., social media, crowdsourced systems, COVID data platforms). Our findings characterize the shifts in trustee (what/who people trust) from information on social media to the social media platform(s), how distrust manifests skepticism in issues of data discrepancy, the insufficient presentation of uncertainty, and how this trust and distrust shift over time. We highlight the deep challenges in existing information infrastructures that influence trust and distrust formation.

著者
Yixuan Zhang
Georgia Institute of Technology, Atlanta, Georgia, United States
Nurul M. Suhaimi
Northeastern University, Boston, Massachusetts, United States
Nutchanon Yongsatianchot
Northeastern University, Boston, Massachusetts, United States
Joseph D. Gaggiano
Georgia Institute of Technology, Atlanta, Georgia, United States
Miso Kim
Northeastern University, Boston, Massachusetts, United States
Shivani A.. Patel
Emory University, Atlanta, Georgia, United States
Yifan Sun
William & Mary, Williamsburg, Virginia, United States
Stacy Marsella
Northeastern University, Boston, Massachusetts, United States
Jacqueline Griffin
Northeastern University, Boston, Massachusetts, United States
Andrea G. Parker
Georgia Tech, Atlanta, Georgia, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3501889

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: COVID Technologies

290
5 件の発表
2022-05-05 18:00:00
2022-05-05 19:15:00