Skip to main content
SpringerLink
Log in

Identifiability as an “Antidote”: Exploring Emotional Contagion and the Role of Anonymity in Twitter Discussions on Misinformation

  • Conference paper
  • First Online:
Social Computing and Social Media: Experience Design and Social Network Analysis (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12774))

Included in the following conference series:

Abstract

Misinformation carries both distorted facts and sophisticated emotional signals. Comparing to facts that could be labeled as true or false, we are more concerned about contaminative negative emotions transferring digitally among users. In this study, we explored an emotional contagion effect among misinformation discussion participants on Twitter. We analyzed the sentiment of 573 tweets in 192 discussion threads. Our result revealed that highly emotional tweets do not have a universal effect on the online discussions, but it affects those individuals with limited social and personal identity cues (i.e., being anonymous). We found that anonymous members of the online discussion are more susceptible to emotional contagions than those are not. We also suggest coping strategies that protect social media users’ emotional well-being during the era COVID-19.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://github.com/philipperemy/name-dataset.

References

  1. Behnke, R.R., Sawyer, C.R., King, P.E.: Contagion theory and the communication of public speaking state anxiety. Commun. Educ. 43, 246–251 (1994)

    Article  Google Scholar 

  2. Brennen, J.S., Simon, F., Howard, P.N., Nielsen, R.K.: Types, sources, and claims of COVID-19 misinformation. Reuters Inst. 7, 3–1 (2020)

    Google Scholar 

  3. Carey, J.M., Chi, V., Flynn, D.J., Nyhan, B., Zeitzoff, T.: The effects of corrective information about disease epidemics and outbreaks: evidence from Zika and yellow fever in Brazil. Sci. Adv. 6(5), eaaw7449 (2020)

    Google Scholar 

  4. Chuai, Y., Zhao, J.: Anger makes fake news viral online. arXiv:2004.10399 (2020)

  5. Coviello, L., et al.: Detecting emotional contagion in massive social networks. PLoS ONE 9(3), e90315 (2014)

    Article  Google Scholar 

  6. Festinger, L., Pepitone, A., Newcomb, T.: Some consequences of de-individuation in a group. J. Abnorm. Soc. Psychol. 47, 382–389 (1952)

    Article  Google Scholar 

  7. Foolen, A.: Word valence and its effects. In: Lüdke, U. (ed.) Emotion in Language, pp. 241–256. John Benjamins, Amsterdam (2015)

    Google Scholar 

  8. Giles, H., Coupland, N., Coupland, J.: Accommodation theory: communication, context, and consequence. In: Giles, H., Coupland, J. (eds.) Contexts of Accommodation: Developments in Applied Sociolinguistics, pp. 1–68 (1991)

    Google Scholar 

  9. Hatfield, E., Cacioppo, J.T., Rapson, R.L.: Emotional contagion. Curr. Dir. Psychol. Sci. 2, 96–100 (1993)

    Article  Google Scholar 

  10. Hutto, C., Gilbert, E.: Vader: A parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, No. 1 (2014)

    Google Scholar 

  11. Kabir, M., Madria, S.: Coronavis: a real-time covid-19 tweets analyzer. arXiv:2004.13932 (2020)

  12. Kiesler, S., Siegel, J., McGuire, T.W.: Social psychological aspects of computer-mediated communication. Am. Psychol. 39, 1123–1134 (1984)

    Article  Google Scholar 

  13. Kramer, A.D., Guillory, J.E., Hancock, J.T.: Experimental evidence of massive-scale emotional contagion through social networks. Proc. Natl. Acad. Sci. 111(24), 8788–8790 (2014)

    Article  Google Scholar 

  14. Kugihara, N.: Effects of aggressive behavior and group size on collective escape in an emergency: a test between a social identity model and deindividuation theory. Br. J. Soc. Psychol. 40(4), 575–598 (2001)

    Article  Google Scholar 

  15. Lee, E.J.: When are strong arguments stronger than weak arguments? Deindividuation effects on message elaboration in computer-mediated communication. Commun. Res. 35(5), 646–665 (2008)

    Article  Google Scholar 

  16. Lee, E.J.: Effects of visual representation on social influence in computer-mediated communication: experimental tests of the social identity model of deindividuation effects. Hum. Commun. Res. 30(2), 234–259 (2004)

    Google Scholar 

  17. Medford, R.J., Saleh, S.N., Sumarsono, A., Perl, T.M., Lehmann, C.U.: An “infodemic”: Leveraging high-volume Twitter data to understand early public sentiment for the coronavirus disease 2019 outbreak. Open Forum Infect. Dis. 7(7), 258 (2020)

    Google Scholar 

  18. Melissa, H.: Misinformation about the coronavirus abounds, but correcting it can backfire”. Los Angeles Times (2020). https://www.latimes.com/science/story/2020-02-08/coronavirus-outbreak-false-information-psychology

  19. Memon, S.A., Carley, K.M.: Characterizing covid-19 misinformation communities using a novel twitter dataset. arXiv:2008.00791 (2020)

  20. National Center for Health Statistics: Mental health household pulse survey (2020). https://www.cdc.gov/nchs/covid19/pulse/mental-health.htm

  21. Paukert, A.L., Pettit, J.W., Amacker, A.: The role of interdependence and perceived similarity in depressed affect contagion. Behav. Ther. 39, 277–285 (2008)

    Article  Google Scholar 

  22. Postmes, T., Spears, R., Lea, M.: Breaching or building social boundaries? SIDE-effects of computer-mediated communication. Commun.Res. 25(6), 689–715 (1998)

    Google Scholar 

  23. Postmes, T., Spears, R., Lea, M.: The formation of group norms in computer-mediated communication. Hum. Commun. Res. 26, 341–371 (2000)

    Article  Google Scholar 

  24. Postmes, T., Spears, R., Sakhel, K., de Groot, D.: social influence in computer-mediated communication: the effects of anonymity on group behavior. Pers. Soc. Psychol. Bull. 27(10), 1243–1254 (2001)

    Article  Google Scholar 

  25. Postmes, T., Spears, R.: Deindividuation and antinormative behavior: a meta-analysis. Psychol. Bull. 123(3), 238–259 (1998)

    Article  Google Scholar 

  26. Rösner, L., Krämer, N.C.: verbal venting in the social web: effects of anonymity and group norms on aggressive language use in online comments. Soc. Media + Soc. 2(3), 1–13 (2016)

    Google Scholar 

  27. Sharma, K., et al.: Coronavirus on social media: analyzing misinformation in Twitter conversations. arXiv:2003, p. 12309 (2020)

  28. Spears, R., Lea, M., Lee, S.: De-individuation and group polarization in computer-mediated communication. Br. J. Soc. Psychol. 29(2), 121–134 (1990)

    Article  Google Scholar 

  29. Spears, R., Postmes, T.: Group identity, social influence, and collective action online. In: Sundar, S.S. (ed.) The Handbook of the Psychology of Communication Technology (2015)

    Google Scholar 

  30. Sun, Y., Chia, S.C., Lu, F., Oktavianus, J.: The battle is on: factors that motivate people to combat anti-vaccine misinformation. Health Commun. 1–10 (2020)

    Google Scholar 

  31. Tausczik, Y., Faasse, K., Pennebaker, J.W., Petrie, K.J.: Public anxiety and information seeking following the H1N1 outbreak: blogs, newspaper articles, and Wikipedia visits. Health Commun. 27(2), 179–185 (2012)

    Article  Google Scholar 

  32. Trautmann, S., et al.: Susceptibility to others’ emotions moderates immediate self-reported and biological stress responses to witnessing trauma. Behav. Res. Ther. 110, 55–63 (2012)

    Article  Google Scholar 

  33. Turner, J. C.: The analysis of social influence. In: Turner, J.C., Hogg, M.A., Oakes, P.J., Reicher, S.D., Wetherell, M.S. (eds.) Rediscovering The Social Group: A Self-Categorization Theory, pp. 68–88 (1987)

    Google Scholar 

  34. Twitter Inc. Staying safe and informed on Twitter (2021). https://blog.twitter.com/en_us/topics/company/2020/covid-19.html#definition

  35. Wheaton, M.G., Prikhidko, A., Messner, G.R.: Is fear of COVID-19 contagious? The effects of emotion contagion and social media use on anxiety in response to the coronavirus pandemic. Front. Psychol. 11 (2020)

    Google Scholar 

  36. Wild, B., Erb, M., Bartels, M.: Are emotions contagious? Evoked emotions while viewing emotionally expressive faces: quality, quantity, time course and gender differences. Psychiatry Res. 102(2), 109–124 (2001)

    Article  Google Scholar 

  37. Xie, X.F., Stone, E., Zheng, R., Zhang, R.G.: The ‘typhoon eye effect’: Determinants of distress during the SARS epidemic. J. Risk Res. 14(9), 1091–1107 (2011)

    Article  Google Scholar 

  38. Yao, M.Z., Flanagin, A.J.: A self-awareness approach to computer-mediated communication. Comput. Hum. Behav. 22(3), 518–544 (2004)

    Article  Google Scholar 

  39. Zimbardo, P.G.: The human choice: Individuation, reason, and order vs. deindividuation, impulse and chaos. In: Arnold, W.J., Levine, D. (eds.) Nebraska Symposium on Motivation, vol. 17, pp. 237–307. University of Nebraska Press, Lincoln, NE (1969)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA

    Chen (Crystal) Chen, Hao Yuan & Mike Z. Yao

Authors
  1. Chen (Crystal) Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hao Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mike Z. Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chen (Crystal) Chen .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Towson University, Towson, MD, USA

    Gabriele Meiselwitz

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chen, C.(., Yuan, H., Yao, M.Z. (2021). Identifiability as an “Antidote”: Exploring Emotional Contagion and the Role of Anonymity in Twitter Discussions on Misinformation. In: Meiselwitz, G. (eds) Social Computing and Social Media: Experience Design and Social Network Analysis . HCII 2021. Lecture Notes in Computer Science(), vol 12774. Springer, Cham. https://doi.org/10.1007/978-3-030-77626-8_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-77626-8_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77625-1

  • Online ISBN: 978-3-030-77626-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation