Evidence map›Paper›PMID 37064998›Full record

ArticleProceedings of the ... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media2021

Well-Being Depends on Social Comparison: Hierarchical Models of Twitter Language Suggest That Richer Neighbors Make You Less Happy.

Salvatore Giorgi, Sharath Chandra Guntuku, Johannes C Eichstaedt, Claire Pajot, H Andrew Schwartz, Lyle H Ungar

Abstract read
In one paragraph

Article in Proceedings of the ... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Salvatore GiorgiUniversity of Pennsylvania.
Sharath Chandra GuntukuUniversity of Pennsylvania.
Johannes C EichstaedtStanford University.
Claire PajotStanford University.
H Andrew SchwartzStony Brook University.
Lyle H UngarUniversity of Pennsylvania.

Funding

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
NIMH NIH HHS R01 MH125702
6 · The paper itself

Abstract

Psychological research has shown that subjective well-being is sensitive to social comparison effects; individuals report decreased happiness when their neighbors earn more than they do. In this work, we use Twitter language to estimate the well-being of users, and model both individual and neighborhood income using hierarchical modeling across counties in the United States (US). We show that language-based estimates from a sample of 5.8 million Twitter users replicate results obtained from large-scale well-being surveys - relatively richer neighbors leads to lower well-being, even when controlling for absolute income. Furthermore, predicting individual-level happiness using hierarchical models (i.e., individuals within their communities) out-predicts standard baselines. We also explore language associated with relative income differences and find that individuals with lower income than their community tend to swear (f*ck, sh*t, b*tch), express anger (pissed, bullsh*t, wtf), hesitation (don't, anymore, idk, confused) and acts of social deviance (weed, blunt, drunk). These results suggest that social comparison robustly affects reported well-being, and that Twitter language analyses can be used to both measure these effects and shed light on their underlying psychological dynamics.

Identifiers

PMID37064998
PMCPMC10099468

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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.