Sangwon Lee
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Articles (16)
Year:
2025
Year:
2025
Year:
2025
Numerous studies have been conducted to identify the factors that predict trust/distrust in science. However, most of these studies are based on closed-ended survey research, which does not allow researchers to gain a more nuanced understanding of the phenomenon. This study integrated survey analysis conducted within the United States with computational text analysis to reveal factors previously obscured by traditional survey methodologies. Even after controlling for political ideology—which has been the most significant explanatory factor in determining trust in science within a survey framework—we found those with concerns over boundary-crossing (i.e. concerns or perceptions that science overlaps with politics, the government, and funding) were less likely to trust science than their counterparts.
Year:
2024
Year:
2024
Year:
2024
Year:
2024
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2024
Year:
2024
Year:
2023
Year:
2023
Year:
2023
Year:
2023
Year:
2023
Year:
2022
Year:
2022
Collaborators (13)
Nuri Kim
Nanyang Technological University (NTU)
Won-Ki Moon
University of Florida
S Mo Jones-Jang
Associate professor
Boston College
Edson Tandoc
Professor
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Kevin Munger
European University Institute
Sebastián Valenzuela
Chief Science Officer
International Panel on the Information Environment (IPIE)
Jihyang Choi
Ewha Womans University
Saifuddin Ahmed
Nanyang Technological University (NTU)
Seungahn Nah
University of Oregon
Marshall Taylor
Assistant Professor
University of New Mexico
Hoyong Jung
Associate Professor
Kookmin University
Trevor Diehl
Central Michigan University
Myojung Chung
Assistant Professor
Northeastern University
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