Peer-Reviewed Publication
Front Soc Psychol2024;2January 1, 2024Journal Article
Quantifying generalized trust in individuals and counties using language.
Salvatore Giorgi1, Jason Jeffrey Jones2, Anneke Buffone3, Johannes C Eichstaedt4, Patrick Crutchley5, David B Yaden6, Jeanette Elstein3, Mohammadzaman Zamani7, Jennifer Kregor3, Laura Smith3, Martin E P Seligman3, Margaret L Kern8, Lyle H Ungar1, H Andrew Schwartz7
1Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.
2Department of Sociology, Stony Brook University, Stony Brook, NY, United States.
3Department of Psychology, University of Pennsylvania, Philadelphia, PA, United States.
4Department of Psychology, Stanford University, Stanford, CA, United States.
5SonderMind, Denver, CO, United States.
6Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
7Department of Computer Science, Stony Brook University, Stony Brook, NY, United States.
8Melbourne Graduate School of Education, University of Melbourne, Parkville, VIC, Australia.
Abstract
Trust is predictive of civic cooperation and economic growth. Recently, the U.S. public has demonstrated increased partisan division and a surveyed decline in trust in institutions. There is a need to quantify individual and community levels of trust unobtrusively and at scale. Using observations of language across more than 16,000 Facebook users, along with their self-reported generalized trust s…
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