Evidence map›Paper›PMID 41199881›Full record

ArticleFrontiers in social psychology2024

Quantifying generalized trust in individuals and counties using language.

Salvatore Giorgi, Jason Jeffrey Jones, Anneke Buffone, Johannes C Eichstaedt, Patrick Crutchley, David B Yaden, Jeanette Elstein, Mohammadzaman Zamani, Jennifer Kregor, Laura Smith and 4 more

Abstract read
In one paragraph

Article in Frontiers in social psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Salvatore GiorgiDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.
Jason Jeffrey JonesDepartment of Sociology, Stony Brook University, Stony Brook, NY, United States.
Anneke BuffoneDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, United States.
Johannes C EichstaedtDepartment of Psychology, Stanford University, Stanford, CA, United States.
Patrick CrutchleySonderMind, Denver, CO, United States.
David B YadenDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Jeanette ElsteinDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, United States.
Mohammadzaman ZamaniDepartment of Computer Science, Stony Brook University, Stony Brook, NY, United States.
Jennifer KregorDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, United States.
Laura SmithDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, United States.
Martin E P SeligmanDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, United States.
Margaret L KernMelbourne Graduate School of Education, University of Melbourne, Parkville, VIC, Australia.
Lyle H UngarDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.
H Andrew SchwartzDepartment of Computer Science, Stony Brook University, Stony Brook, NY, United States.

Funding

Large-scale Data Scientific Assessment of Unhealthy Alcohol Consumption Among Front-Line Restaurant WorkersR01AA028032 · NIAAA · STATE UNIVERSITY NEW YORK STONY BROOK · PI SCHWARTZ, HANSEN ANDREW · 2020 to 2023
$2.5M
SCH: Advancing Language-based Analyses of Social Media to Reliably Monitor Variation in PopulationR01MH125702 · NIMH · STATE UNIVERSITY NEW YORK STONY BROOK · PI EICHSTAEDT, JOHANNES C., SCHWARTZ, HANSEN ANDREW · 2021 to 2024
$1.2M
NIAAA NIH HHS R01 AA028032NIMH NIH HHS R01 MH125702
6 · The paper itself

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 score, we develop and evaluate a language-based assessment of generalized trust. We then apply the assessment to more than 1.6 billion geotagged tweets collected between 2009 and 2015 and derive estimates of trust across 2,041 U.S. counties. We find generalized trust was associated with more affiliative words (

Indexed as

data driven approachesgeneralized trustlanguage analysissocial epidemiologysocial media

Identifiers

PMID41199881
PMCPMC12588161

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.