Skip to main content

Burstiness in Emotions: A Case Study on Collective Affective Responses in Italian Soccer Fandoms

  • Conference paper
  • First Online:
Social Networks Analysis and Mining (ASONAM 2024)

Abstract

The bursty nature of emotions is rarely investigated outside cognitive and psychological studies. Therefore this work addresses a gap in the literature, investigating the phenomenon of emotional burstiness using tools from the analysis of complex systems, and considering as case-study soccer fans’ affective responses on social media. We reconstruct collective reactions on Instagram posts from official accounts of 40 Italian football teams during the first round of the 2023–2024 season – 20 teams from Serie B (the second tier of Italian Football) and the 20 most followed teams in Serie C (the third tier). With this data, we build sequences of emotional signals for four types of emotions: joy, anger, sadness, and fear. Our analysis reveals trends of anti-burstiness in expressions of joy among users, reflecting fans’ consistent support for teams, occasionally interspersed by bursts of anger and sadness, with no signals of fear. This preliminary investigation provides insights for the understanding of emotional dynamics in online discussions and team supporting in soccer leagues.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://en.wikipedia.org/wiki/2023-24_Serie_B.

  2. 2.

    https://en.wikipedia.org/wiki/2023-24_Serie_C.

  3. 3.

    https://github.com/MilaNLProc/feel-it.

  4. 4.

    https://en.wikipedia.org/wiki/2023-24_Brescia_Calcio_season.

References

  1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th edn. Text Rev. (2002)

    Google Scholar 

  2. Bianchi, F., Nozza, D., Hovy, D.: FEEL-IT: emotion and sentiment classification for the Italian language. In: Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics (2021)

    Google Scholar 

  3. Bak, P., et al.: Unified scaling law for earthquakes. Phys. Rev. Lett. 88(17), 178501 (2002)

    Article  MATH  Google Scholar 

  4. Balsamo, D., et al.: The pursuit of peer support for opioid use recovery on Reddit. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 17 (2023)

    Google Scholar 

  5. Barabasi, A.-L.: The origin of bursts and heavy tails in human dynamics. Nature 435(7039), 207–211 (2005)

    Article  MATH  Google Scholar 

  6. Cauteruccio, F., Kou, Y.: Investigating the emotional experiences in eSports spectatorship: the case of League of Legends. Inf. Process. Manage. 60(6), 103516 (2023)

    Article  Google Scholar 

  7. Cencetti, G., et al.: Temporal properties of higher-order interactions in social networks. Sci. Rep. 11(1), 7028 (2021)

    Article  MATH  Google Scholar 

  8. Cinelli, M., et al.: Dynamics of online hate and misinformation. Sci. Rep. 11(1), 22083 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  9. Darst, R.K., et al.: Detection of timescales in evolving complex systems. Sci. Rep. 6(1), 39713 (2016)

    Article  MATH  Google Scholar 

  10. Devlin, J., et al.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

  11. Ekman, P.: Facial expression and emotion. Am. Psychol. 48(4), 384 (1993)

    Article  MATH  Google Scholar 

  12. Garas, A., et al.: Emotional persistence in online chatting communities. Sci. Rep. 2(1), 1–8 (2012)

    Article  MATH  Google Scholar 

  13. Goldenberg, A., et al.: Collective emotions. Curr. Dir. Psychol. Sci. 29(2), 154–160 (2020)

    Article  MATH  Google Scholar 

  14. Goh, K.-I., Barabási, A.-L.: Burstiness and memory in complex systems. Europhys. Lett. 81(4), 48002 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  15. Heuer, H., et al.: Auditing the biases enacted by YouTube for political topics in Germany. Proc. Mensch und Comput. 2021, 456–468 (2021)

    MATH  Google Scholar 

  16. Joseph, S.M., et al.: Cognitive network neighborhoods quantify feelings expressed in suicide notes and Reddit mental health communities. Physica A: Stat. Mech. Appl. 610, 128336 (2023)

    Article  MATH  Google Scholar 

  17. Karsai, M., Jo, H.-H., Kaski, K.: Bursty Human Dynamics. SC, Springer, Cham (2018). https://doi.org/10.1007/978-3-319-68540-3

    Book  MATH  Google Scholar 

  18. Kim, E.-K., Jo, H.-H.: Measuring burstiness for finite event sequences. Phys. Rev. E 94(3), 032311 (2016)

    Article  MATH  Google Scholar 

  19. Lazarus, R.S., Folkman, S.: Stress, Appraisal, and Coping. Springer, Cham (1984). https://doi.org/10.1007/978-3-030-39903-0_215

  20. Mainwaring, Ed., Clark, T.: ‘We’re shit and we know we are’: identity, place and ontological security in lower league football in England. Soccer Soc. 13(1), 107–123 (2012)

    Google Scholar 

  21. Nizzoli, L., et al.: Coordinated behavior on social media in 2019 UK general election. Proc. Int. AAAI Conf. Web Soc. Media 15, 2021 (2019)

    Google Scholar 

  22. Pacheco, D.F., et al.: Characterization of Football Supporters from Twitter Conversations. WI (2016)

    Google Scholar 

  23. Pappalardo, L., et al.: PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach. ACM Trans. Intell. Syst. Technol. (TIST) 10(5), 1–27 (2019)

    Article  MATH  Google Scholar 

  24. Scherer, K.R.: Affect bursts. Emotions, pp. 175–208. Psychology Press (2014)

    Google Scholar 

  25. Schleiss, M., Smith, J.A.: Two simple metrics for quantifying rainfall intermittency: the burstiness and memory of interamount times. J. Hydrometeorol. 17(1), 421–436 (2016)

    Article  Google Scholar 

  26. Schröder, M.: Experimental study of affect bursts. Speech Commun. 40(1–2), 99–116 (2003)

    Article  MATH  Google Scholar 

  27. Starnini, M., Baronchelli, A., Pastor-Satorras, R.: Modeling human dynamics of face-to-face interaction networks. Phys. Rev. Lett. 110(16), 168701 (2013)

    Article  MATH  Google Scholar 

  28. Stella, M., Ferrara, E., De Domenico, M.: Bots increase exposure to negative and inflammatory content in online social systems. Proc. Nat. Acad. Sci. 115(49), 12435–12440 (2018)

    Article  Google Scholar 

  29. Stella, M.: Cognitive network science for understanding online social cognitions: a brief review. Top. Cogn. Sci. 14(1), 143–162 (2022)

    Article  MATH  Google Scholar 

Download references

Acknowledgment

This project was funded by SoBigData.it which receives funding from the European Union – NextGenerationEU – National Recovery and Resilience Plan (Piano Nazionale di Ripresa e Resilienza, PNRR) – Project: “SoBigData.it – Strengthening the Italian RI for Social Mining and Big Data Analytics” – Prot. IR0000013 – Avviso n. 3264 del 28/12/2021.

Author information

Authors and Affiliations

Authors

Contributions

S.C. conceptualized the research, conducted the experiments, made the plots, wrote the code and the paper. G.M. conceptualized the research, supervised the experiments and wrote the paper. E.F. supervised the research and wrote the paper.

Corresponding author

Correspondence to Salvatore Citraro .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Citraro, S., Mauro, G., Ferragina, E. (2025). Burstiness in Emotions: A Case Study on Collective Affective Responses in Italian Soccer Fandoms. In: Aiello, L.M., Chakraborty, T., Gaito, S. (eds) Social Networks Analysis and Mining. ASONAM 2024. Lecture Notes in Computer Science, vol 15211. Springer, Cham. https://doi.org/10.1007/978-3-031-78541-2_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-78541-2_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-78540-5

  • Online ISBN: 978-3-031-78541-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics