IDEAS home Printed from https://ideas.repec.org/a/eee/spomar/v22y2019i3p348-362.html
   My bibliography  Save this article

Spectators’ emotional responses in tweets during the Super Bowl 50 game

Author

Listed:
  • Chang, Yonghwan

Abstract

The author explored spectators’ emotional reactions manifested on social media. By using Twitter search application programming interface, 328,000 real-time tweets posted by fans of the Panthers and the Broncos during the Super Bowl 50 game were collected. The lexicon-based text mining approach (a big data analysis in social media analytics) was employed to classify tweets into five different emotions. The findings indicated that spectators expressed positive emotions when their team scored; conversely, they expressed negative emotions when the opposite team scored. Interestingly, spectators became habituated with each subsequent score from either of their preferred teams, which resulted in fewer expressions of emotions. However, when a team scored soon after the opposite team scored, fans expressed a surge of positive or negative emotions, accordingly. The results supported both the theories of affective disposition and opponent-process. Spectators’ simultaneous experience of positive and negative emotions may contribute to fans’ satisfaction, continued patronage, and mental health.

Suggested Citation

  • Chang, Yonghwan, 2019. "Spectators’ emotional responses in tweets during the Super Bowl 50 game," Sport Management Review, Elsevier, vol. 22(3), pages 348-362.
  • Handle: RePEc:eee:spomar:v:22:y:2019:i:3:p:348-362
    DOI: 10.1016/j.smr.2018.04.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1441352318301487
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.smr.2018.04.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tingting Nian & Yuheng Hu & Cheng Chen, 2021. "Examining the Impact of Television-Program-Induced Emotions on Online Word-of-Mouth Toward Television Advertising," Information Systems Research, INFORMS, vol. 32(2), pages 605-632, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:spomar:v:22:y:2019:i:3:p:348-362. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/716936/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.