The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Conservatives report, but liberals display, greater happiness
Abstract
Be mindful of a self-reported gap: Happiness is a notoriously hard to pin down quantity possibly best described by the phrase, “I know it when I see it.” Self-reported ratings of happiness are generally higher for political conservatives in the United States than for those with more liberal leanings. Wojcik et al. examined three data sets based on behavioral measures, such as tweets and smiles. Despite self-reported claims to the contrary, liberals exhibited more happiness than their more conservative counterparts. For instance, as judged from their photographs on a business-oriented social network, more employees of the New York Times smiled genuinely than did those of the Wall Street Journal . Science , this issue p. 1243
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Cites
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Cited by
Ideological Asymmetries and the Essence of Political Psychology
Jost, J. T. (2017) · Political Psychology · doi:10.1111/pops.12407 · Cited by 696
Jost, J. T. (2019) · British Journal of Social Psychology · doi:10.1111/bjso.12297 · Cited by 567
Ditto, P. H., Liu, B. S., Clark, C. J., Wojcik, S. P., Chen, E. E., Grady, R. H., Celniker, J. B., & Zinger, J. F. (2019) · Perspectives on Psychological Science · doi:10.1177/1745691617746796 · Cited by 535
Self-citationLanguage-based personality: a new approach to personality in a digital world
Boyd, R. L., & Pennebaker, J. W. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.07.017 · Cited by 296
GPT is an effective tool for multilingual psychological text analysis
Rathje, S., Mirea, D.-M., Sucholutsky, I., Marjieh, R., Robertson, C. E., & Van Bavel, J. J. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2308950121 · Cited by 297
Metadata
- Authors
- Wojcik, S. P., Hovasapian, A., Graham, J., Motyl, M., & Ditto, P. H.
- Venue
- Science
- Published
- 2015-03-13
- Volume
- 347
- Issue
- 6227
- Pages
- 1243-1246
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2026216144
- Cited by
- 167
- References
- 6
- FWCI
- 25.03
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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