Social media users produce more affect that supports cultural values, but are more influenced by affect that violates cultural values
Open accessAbstract
Although social media plays an increasingly important role in communication around the world, social media research has primarily focused on Western users. Thus, little is known about how cultural values shape social media behavior. To examine how cultural affective values might influence social media use, we developed a new sentiment analysis tool that allowed us to compare the affective content of Twitter posts in the United States (55,867 tweets, 1,888 users) and Japan (63,863 tweets, 1,825 users). Consistent with their respective cultural affective values, U.S. users primarily produced positive (vs. negative) posts, whereas Japanese users primarily produced low (vs. high) arousal posts. Contrary to cultural affective values, however, U.S. users were more influenced by changes in others' high arousal negative (e.g., angry) posts, whereas Japanese were more influenced by changes in others' high arousal positive (e.g., excited) posts. These patterns held after controlling for differences in baseline exposure to affective content, and across different topics. Together, these results suggest that across cultures, while social media users primarily produce content that supports their affective values, they are more influenced by content that violates those values. These findings have implications for theories about which affective content spreads on social media, and for applications related to the optimal design and use of social media platforms around the world. (PsycInfo Dat…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Individuals are more willing and likely to post information on social media platforms that aligns with their beliefs or values.
“Hence, they are more willing and likely to post information on social media platforms that aligns with their beliefs or values [80].”
From What Influences Users’ Intention to Share Works in Designer-Driven User-Generated Content Communities? A Study Based on Self-Determination Theory (2023) · cites this paper as [80]
Cites
The spread of true and false news online
Vosoughi, S., Roy, D., & Aral, S. (2018) · Science · doi:10.1126/science.aap9559 · Cited by 8,847 · see citing works
The ripple effect: emotional contagion and its influence on group behavior
Barsade, S. G. (2002) · Administrative Science Quarterly · doi:10.2307/3094912 · Cited by 3,361 · see citing works
Is there a universal need for positive self-regard?
Heine, S. J., Lehman, D. R., Markus, H. R., & Kitayama, S. (1999) · Psychological Review · doi:10.1037/0033-295x.106.4.766 · Cited by 2,247 · see citing works
Sentiment strength detection in short informal text
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., & Kappas, A. (2010) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21416 · Cited by 1,449 · see citing works
Self-citationSocial comparison, social media, and self-esteem.
Vogel, E. A., Rose, J. P., Roberts, L. R., & Eckles, K. (2014) · Psychology of Popular Media Culture · doi:10.1037/ppm0000047 · Cited by 1,418 · see citing works
Emotion shapes the diffusion of moralized content in social networks
Brady, W. J., Wills, J. A., Jost, J. T., Tucker, J. A., & Van Bavel, J. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1618923114 · Cited by 1,396 · see citing works
Deviance or uniqueness, harmony or conformity: A cultural analysis
Kim, H., & Markus, H. R. (1999) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.77.4.785 · Cited by 1,216 · see citing works
Moral outrage in the digital age
Crockett, M. J. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0213-3 · Cited by 618 · see citing works
Kitayama, S., & Markus, H. R. (2000) · Culture and Subjective Well-Being · doi:10.7551/mitpress/2242.003.0010 · Cited by 504 · see citing works
How effective is online outrage?
Brady, W. J., & Crockett, M. J. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.11.004 · Cited by 79 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Algorithm-mediated social learning in online social networks
Brady, W. J., Jackson, J. C., Lindström, B., & Crockett, M. J. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.06.008 · Cited by 132 · see citing works
People think that social media platforms do (but should not) amplify divisive content
Rathje, S., Robertson, C., Brady, W. J., & Van Bavel, J. J. (2024) · Perspectives on Psychological Science · doi:10.1177/17456916231190392 · Cited by 59 · see citing works
Embedding Societal Values into Social Media Algorithms
Bernstein, M., Christin, A., Hancock, J., Hashimoto, T., Jia, C., Lam, M., Meister, N., Persily, N., Piccardi, T., Saveski, M., et al. (2023) · Journal of Online Trust and Safety · doi:10.54501/jots.v2i1.148 · Cited by 31 · see citing works
Self-citationSong, H., Wei, J., & Jiang, Q. (2023) · Systems · doi:10.3390/systems11110540 · Cited by 13 · see citing works
- Authors
- Hsu, T. W., Niiya, Y., Thelwall, M., Ko, M., Knutson, B., & Tsai, J. L.
- Affiliations
- Stanford University (US)
- Hosei University (JP)
- University of Wolverhampton (GB)
- Venue
- Journal of Personality and Social Psychology
- Published
- 2021-11
- Volume
- 121
- Issue
- 5
- Pages
- 969-983
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W3187942383
- Cited by
- 50
- References
- 10
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 15 · 2023: 14 · 2022: 3
- FWCI
- 7.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Personality and Social Psychology (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton) (acceptedVersion, cc-by-nc-nd)
- Funders
- National Science Foundation (1732963)
- Topics
- Social Sciences › Psychology › Social Psychology › Cultural Differences and Values
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Keywords
- social media use, cultural values, emotional value, emotional content, sentiment analysis, Twitter, cross-cultural comparison, United States, Japan, emotional arousal, emotional contagion, emotional expression
- MeSH terms
- Sentiment Analysis, Arousal, Communication, Humans, Japan, United States, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
