Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Overperception of moral outrage in online social networks inflates beliefs about intergroup hostility

Nature Human Behaviour volume 7, pages 917–927 (2023)Cite this article

Subjects

Abstract

As individuals and political leaders increasingly interact in online social networks, it is important to understand the dynamics of emotion perception online. Here, we propose that social media users overperceive levels of moral outrage felt by individuals and groups, inflating beliefs about intergroup hostility. Using a Twitter field survey, we measured authors’ moral outrage in real time and compared authors’ reports to observers’ judgements of the authors’ moral outrage. We find that observers systematically overperceive moral outrage in authors, inferring more intense moral outrage experiences from messages than the authors of those messages actually reported. This effect was stronger in participants who spent more time on social media to learn about politics. Preregistered confirmatory behavioural experiments found that overperception of individuals’ moral outrage causes overperception of collective moral outrage and inflates beliefs about hostile communication norms, group affective polarization and ideological extremity. Together, these results highlight how individual-level overperceptions of online moral outrage produce collective overperceptions that have the potential to warp our social knowledge of moral and political attitudes.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Overview of Twitter field study method.
Fig. 2: Evidence of overperception of individuals’ moral outrage on Twitter.
Fig. 3: Observers’ overperception of outrage is positively associated with their daily political social media use.
Fig. 4: Depiction of newsfeed manipulation in a mock social media environment.
Fig. 5: Overperception of outrage in newsfeeds amplifies perceptions of collective outrage and beliefs about outrage norms.

Similar content being viewed by others

Data availability

All de-identified data are available at https://osf.io/gtwsk/ and https://doi.org/10.17605/OSF.IO/GTWSK. Data may not be used for commercial purposes.

Code availability

All analysis scripts are available at https://osf.io/gtwsk/ and https://doi.org/10.17605/OSF.IO/GTWSK. Code may not be used for commercial purposes.

References

  1. Rini, R. Social Media Disinformation and the Security Threat to Democratic Legitimacy (NATO Association of Canada, 2019); https://natoassociation.ca/wp-content/uploads/2019/10/NATO-publication-.pdf

  2. Raz, J. The Morality of Freedom (Clarendon Press, 1986).

  3. Tattersall, A. Power in Coalition: Strategies for Strong Unions and Social Change (Routledge, 2020).

  4. Lazer, D. M. J. et al. The science of fake news. Science 359, 1094–1096 (2018).

    Article  CAS  PubMed  Google Scholar 

  5. Starbird, K., Arif, A. & Wilson, T. Disinformation as collaborative work: surfacing the participatory nature of strategic information operations. Proc. ACM Hum. Comput. Interact. 3, 1–127 (2019).

    Article  Google Scholar 

  6. Bail, C. Breaking the Social Media Prism: How to Make Our Platforms Less Polarizing (Princeton Univ. Press, 2021).

  7. Salerno, J. M. & Peter-Hagene, L. C. The interactive effect of anger and disgust on moral outrage and judgments. Psychol. Sci. 24, 2069–2078 (2013).

    Article  PubMed  Google Scholar 

  8. Haidt, J. in Handbook of Affective Sciences (Davidson, R. J. et al.) 852–870 (Oxford Univ. Press, 2003).

  9. Brady, W. J., Crockett, M. J. & Van Bavel, J. J. The MAD model of moral contagion: the role of motivation, attention, and design in the spread of moralized content online. Perspect. Psychol. Sci. 15, 978–1010 (2020).

    Article  PubMed  Google Scholar 

  10. Spring, V. L., Cameron, C. D. & Cikara, M. The upside of outrage. Trends Cogn. Sci. 22, 1067–1069 (2018).

    Article  PubMed  Google Scholar 

  11. Brady, W. J. & Crockett, M. J. How effective is online outrage? Trends Cogn. Sci. 23, 79–80 (2019).

    Article  PubMed  Google Scholar 

  12. Lengel, R. H. & Daft, R. L. The selection of communication media as an executive skill. Acad. Manag. Perspect. 2, 225–232 (1988).

    Article  Google Scholar 

  13. Weisband, S. & Atwater, L. Evaluating self and others in electronic and face-to-face groups. J. Appl. Psychol. 84, 632–639 (1999).

    Article  Google Scholar 

  14. Byron, K. Carrying too heavy a load? The communication and miscommunication of emotion by email. Acad. Manag. Rev. 33, 309–327 (2008).

    Article  Google Scholar 

  15. Walther, J. B. & D’Addario, K. P. The impacts of emoticons on message interpretation in computer-mediated communication. Soc. Sci. Comput. Rev. 19, 324–347 (2001).

    Article  Google Scholar 

  16. Brady, W. J., McLoughlin, K., Doan, T. N. & Crockett, M. How social learning amplifies moral outrage expression in online social networks. Sci. Adv. 7, eabe5641 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Brady, W.J. et al. Algorithm-mediated social learning in online social networks. Preprint at OSF preprints. https://doi.org/10.31219/osf.io/yw5ah (2023).

  18. Brady, W. J. & Van Bavel, J. J. Social identity shapes antecedents and functional outcomes of moral emotion expression in online networks. Preprint at OSF preprints https://doi.org/10.31219/osf.io/dgt6u (2021).

  19. Jordan, J. J. & Rand, D. G. Signaling when no one is watching: a reputation heuristics account of outrage and punishment in one-shot anonymous interactions. J. Personal. Soc. Psychol. 118, 57 (2019).

    Article  Google Scholar 

  20. Jordan, J. J., Hoffman, M., Bloom, P. & Rand, D. G. Third-party punishment as a costly signal of trustworthiness. Nature 530, 473–476 (2016).

    Article  PubMed  Google Scholar 

  21. Crockett, M. J. Moral outrage in the digital age. Nat. Hum. Behav. 1, 769–771 (2017).

    Article  CAS  PubMed  Google Scholar 

  22. Brady, W. J., Wills, J. A., Jost, J. T., Tucker, J. A. & Van Bavel, J. J. Emotion shapes the diffusion of moralized content in social networks. Proc. Natl Acad. Sci. USA 114, 7313–7318 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Degroot, M. H. Reaching a consensus. J. Am. Stat. Assoc. 69, 118–121 (1974).

    Article  Google Scholar 

  24. Goldenberg, A., Weisz, E., Sweeny, T. D., Cikara, M. & Gross, J. J. The crowd-emotion-amplification effect. Psychol. Sci. 32, 437–450 (2021).

    Article  PubMed  Google Scholar 

  25. McClain, C. 70% of U.S. Social Media Users Never or Rarely Post or Share about Political, Social Issues (Pew Research Center, 2021); https://www.pewresearch.org/fact-tank/2021/05/04/70-of-u-s-social-media-users-never-or-rarely-post-or-share-about-political-social-issues/

  26. Duggan, M. & Smith, A. The Political Environment on Social Media (Pew Research Center, 2016); https://www.pewresearch.org/internet/2016/10/25/the-political-environment-on-social-media/

  27. Huszár, F. et al. Algorithmic amplification of politics on Twitter. Proc. Natl Acad. Sci. USA 119, e2025334119 (2022).

    Article  PubMed  Google Scholar 

  28. Chakradhar, S. More Internal Documents Show how Facebook’s Algorithm Prioritized Anger and Posts that Triggered it (Nieman Lab, 2021); https://www.niemanlab.org/2021/10/more-internal-documents-show-how-facebooks-algorithm-prioritized-anger-and-posts-that-triggered-it/

  29. Chowdhury, R. Examining algorithmic amplification of political content on Twitter. Twitter https://blog.twitter.com/en_us/topics/company/2021/rml-politicalcontent (2021).

  30. Shamir, J. & Shamir, M. Pluralistic ignorance across issues and over time: information cues and biases. Public Opin. Q. 61, 227–260 (1997).

    Article  Google Scholar 

  31. Prentice, D. A. & Miller, D. T. Pluralistic ignorance and alcohol use on campus: some consequences of misperceiving the social norm. J. Pers. Soc. Psychol. 64, 243–256 (1993).

    Article  CAS  PubMed  Google Scholar 

  32. Lees, J. M. & Cikara, M. Understanding and Combating Misperceived Polarization. Phil. Trans. R. Soc. B 376, 20200143 (2020).

  33. Wilson, A. E., Parker, V. A. & Feinberg, M. Polarization in the contemporary political and media landscape. Curr. Opin. Behav. Sci. 34, 223–228 (2020).

    Article  Google Scholar 

  34. Levendusky, M. S. & Malhotra, N. (Mis)perceptions of partisan polarization in the American public. Public Opin. Q. 80, 378–391 (2016).

    Article  Google Scholar 

  35. Enders, A. M. & Armaly, M. T. The differential effects of actual and perceived polarization. Polit. Behav. 41, 815–839 (2019).

    Article  Google Scholar 

  36. Ronson, J. So You’ve Been Publicly Shamed (Penguin, 2015).

  37. Peters, K. & Kashima, Y. A multimodal theory of affect diffusion. Psychol. Bull. 141, 966–992 (2015).

    Article  PubMed  Google Scholar 

  38. Lerman, K., Yan, X. & Wu, X.-Z. The ‘majority illusion’ in social networks. PLoS ONE 11, e0147617 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Alipourfard, N., Nettasinghe, B., Abeliuk, A., Krishnamurthy, V. & Lerman, K. Friendship paradox biases perceptions in directed networks. Nat. Commun. 11, 707 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Schöne, J. P., Parkinson, B. & Goldenberg, A. Negativity spreads more than positivity on Twitter after both positive and negative political situations. Affect. Sci. 2, 379–390 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Kuran, T. Preference falsification, policy continuity and collective conservatism. Econ. J. 97, 642–665 (1987).

    Article  Google Scholar 

  42. Noelle‐Neumann, E. The spiral of silence a theory of public opinion. J. Commun. 24, 43–51 (1974).

    Article  Google Scholar 

  43. Hampton, K., Rainie, L., Dwyer, M., Shin, I. & Purcell, K. Social Media and the ‘Spiral of Silence’ (Pew Research Center, 2014); https://www.pewresearch.org/internet/2014/08/26/social-media-and-the-spiral-of-silence/

  44. Lees, J. & Cikara, M. Inaccurate group meta-perceptions drive negative out-group attributions in competitive contexts. Nat. Hum. Behav. 4, 279–286 (2020).

    Article  PubMed  Google Scholar 

  45. Kozyreva, A., Lorenz-Spreen, P., Hertwig, R., Lewandowsky, S. & Herzog, S. M. Public attitudes towards algorithmic personalization and use of personal data online: evidence from Germany, Great Britain, and the United States. Humanit. Soc. Sci. Commun. 8, 117 (2021).

  46. Rader, E. Examining user surprise as a symptom of algorithmic filtering. Int. J. Hum. Comput. Stud. 98, 72–88 (2017).

    Article  Google Scholar 

  47. Berlo, D. K. The Process of Communication: An Introduction to Theory and Practice (Holt, Rinehart & Winston, 1960).

  48. Guess, A., Munger, K., Nagler, J. & Tucker, J. How accurate are survey responses on social media and politics? Polit. Commun. 36, 241–258 (2019).

    Article  Google Scholar 

Download references

Acknowledgements

We thank members of the Crockett Lab for valuable feedback throughout the project. We also thank members of the Greene and Cushman Moral Psychology Research Lab, members of the Deghani Computational Social Science Laboratory and members of the Willer Polarization and Social Change Lab for feedback from a laboratory presentation of this work. We thank J. Lees for feedback on analyses. We thank A. Goolsbee who contributed to the construction of the observer-phase survey in studies 1–3. We thank A. Blevins for designing Figs. 1 and 4. This project was supported by the National Science Foundation, award no. 1808868 (awarded to W.J.B.) and the Democracy Fund, award no. R-201809-03031 (awarded to W.J.B. and M.J.C.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Kellogg School of Management, Northwestern University, Evanston, IL, USA

    William J. Brady

  2. Department of Psychology, Yale University, New Haven, CT, USA

    William J. Brady, Killian L. McLoughlin, Kara F. Luo, Maria Gendron & M. J. Crockett

  3. Department of Psychology, Princeton University, Princeton, NJ, USA

    Killian L. McLoughlin & M. J. Crockett

  4. School of Public and International Affairs, Princeton University, Princeton, NJ, USA

    Killian L. McLoughlin

  5. Department of Statistics and Data Science, Yale University, New Haven, CT, USA

    Mark P. Torres

  6. University Center for Human Values, Princeton University, Princeton, NJ, USA

    M. J. Crockett

Authors
  1. William J. Brady
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Killian L. McLoughlin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mark P. Torres
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kara F. Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Maria Gendron
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. J. Crockett
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

W.J.B., K.L.M., M.G. and M.J.C. designed the research. W.J.B., K.L.M., M.T. and K.L. performed the research. W.J.B. analysed the data with input from M.J.C. W.J.B. wrote the paper with input from M.J.C. and all authors contributed to revisions.

Corresponding authors

Correspondence to William J. Brady or M. J. Crockett.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Human Behaviour thanks Robb Willer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary analyses, Figs. 1–7 and Table 1.

Reporting Summary

Peer Review File

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brady, W.J., McLoughlin, K.L., Torres, M.P. et al. Overperception of moral outrage in online social networks inflates beliefs about intergroup hostility. Nat Hum Behav 7, 917–927 (2023). https://doi.org/10.1038/s41562-023-01582-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-023-01582-0

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing