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Live It Up: Analyzing Emotions and Language Use in Tweets during the Soccer World Cup Finals

Published: 26 June 2019 Publication History

Abstract

In this paper, we present a study to identify similarities and differences in how users express themselves on Twitter during two editions of the most watched sports events in the world, the finals of the FIFA Soccer World Cup of 2014 and 2018. Our findings suggest in 2014 users tended to post more negative content than in 2018, while less hateful and offensive messages were posted in 2018 than in 2014. This study also showcases the challenges of performing analysis of emotional reactions on sports-related posts due to the specificity of the colorful language employed by the fans.

References

[1]
S. Aloufi, F. Alzamzami, M. Hoda, and A. Saddik. 2018. Soccer Fans Sentiment through the Eye of Big Data: The UEFA Champions League as a Case Study. In Proc of. MIPR.
[2]
P. Cavalin, M. Gatti, T. Moraes, F. Oliveira, C. Pinhanez, A. Rademaker, and R. Paula. 2015. A scalable architecture for real-time analysis of microblogging data. IBM Journal of Research and Development, Vol. 59, 2/3 (March 2015), 16:1--16:10.
[3]
J. Chon, R. Raymond, H. Wang, and F. Wang. 2015. Modeling Flu Trends with Real-Time Geo-tagged Twitter Data Streams. In Wireless Algorithms, Systems, and Applications. Springer, 60--69.
[4]
M. Conover, J. Ratkiewicz, M. Francisco, B. Gonccalves, A. Flammini, and F. Menczer. 2011. Political Polarization on Twitter. In Proc. of ICWSM'11.
[5]
T. Davidson, D. Warmsley, M. Macy, and I. Weber. 2017. Automated Hate Speech Detection and the Problem of Offensive Language. In Proc. of ICWSM'17.
[6]
E. Fast, B. Chen, and M. Bernstein. 2016. Empath: Understanding Topic Signals in Large-Scale Text. In Proc. of the CHI.
[7]
T. Gil-Lopez, S. Ahmed, and D. Taylor. 2017. Understanding Fandom in the Multilingual Internet: A Study of “El Clasico” Fans' Commenting Behavior on YouTube. International Journal of Sport Communication, Vol. 10, 1 (2017), 17--33.
[8]
J. Gratch, G. Lucas, N. Malandrakis, E. Szablowski, E. Fessler, and J. Nichols. 2015. GOAALLL!: Using Sentiment in the World Cup to Explore Theories of Emotion. In Proc. of the ACII.
[9]
Chiaku Hanson. 2017. Nigger vs Nigga. (2017). https://www.huffingtonpost.com/chiaku-hanson/nigger-vs-nigga_b_10602798.html
[10]
J. Kim, D. Kim, B. Keegan, H. Kim, S. Kim, and A. Oh. 2015. Social Media Dynamics of Global Co-presence During the 2014 FIFA World Cup. In Proc. of CHI.
[11]
I. Kwok and Y. Wang. 2013. Locate the Hate: Detecting Tweets Against Blacks. Proc. of AAAI.
[12]
Y. Liu, C. Kliman-Silver, and A. Mislove. 2014. The Tweets They Are a-Changin': Evolution of Twitter Users and Behavior. In Proc. of ICWSM'14.
[13]
ARK Carnegie Mellon. 2018. Twitter part-of-speech tagger. (2018). http://www.cs.cmu.edu/ ark/TweetNLP/
[14]
M. Mondal, L. Silva, and F. Benevenuto. 2017. A Measurement Study of Hate Speech in Social Media. In Proc. of the HT.
[15]
Scott Muska. 2018. What happens to your body and brain when you watch football. (2018). https://www.nbcnews.com/better/health/what-happens-your-body-brain-when-you-watch-football-ncna814401
[16]
J. Nichols, J. Mahmud, and C. Drews. 2012. Summarizing Sporting Events Using Twitter. In Proc. of the IUI.
[17]
A. Olteanu, C. Castillo, J. Boy, and K. Varshney. 2018. The Effect of Extremist Violence on Hateful Speech Online. In Proc of the ICWSM.
[18]
A. Olteanu, C. Castillo, F. Diaz, and E. Kiciman. 2016. Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries. (2016). https://ssrn.com/abstract=2886526 Last revised: 29 Mar 2017.
[19]
D. Oshimi. 2015. Emotions of Sports Spectators. Sports Management and Sports Humanities. Springer, Chapter 2, 17--30.
[20]
B. Poblete, J. Guzman, J. Maldonado, and F. Tobar. 2018. Robust Detection of Extreme Events Using Twitter: Worldwide Earthquake Monitoring. IEEE Transactions on Multimedia, Vol. 20, 10 (Oct 2018), 2551--2561.
[21]
C. Simeon and R. Hilderman. 2015. Evaluating the Effectiveness of Hashtags as Predictors of the Sentiment of Tweets. In Discovery Science. Springer, 251--265.
[22]
Y. Wang, J. Callan, and B. Zheng. 2015. Should We Use the Sample? Analyzing Datasets Sampled from Twitter's Stream API. ACM Transactions on the Web, Vol. 9, 3, Article 13 (June 2015), bibinfonumpages23 pages.
[23]
Wikipedia. 2018. Nigga. (2018). https://en.wikipedia.org/wiki/Nigga
[24]
Y. Yu and X. Wang. 2015. World Cup 2014 in the Twitter World: A big data analysis of sentiments in U.S. sports fans' tweets. Computers in Human Behaviour, Vol. 48, C (jul 2015), 392--400.

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cover image ACM Conferences
WebSci '19: Proceedings of the 10th ACM Conference on Web Science
June 2019
395 pages
ISBN:9781450362023
DOI:10.1145/3292522
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 26 June 2019

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Author Tags

  1. audience reaction
  2. hate speech
  3. language use patterns
  4. sentiment
  5. twitter
  6. world cup

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WebSci '19
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WebSci '19: 11th ACM Conference on Web Science
June 30 - July 3, 2019
Massachusetts, Boston, USA

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WebSci '19 Paper Acceptance Rate 41 of 130 submissions, 32%;
Overall Acceptance Rate 245 of 933 submissions, 26%

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