Abstract
Messages from social media are increasingly being mined to extract useful information and to detect trends. These can relate to matters as serious as earthquakes and wars or as trivial as haircuts and cats. Football remains one of the world’s most popular sports, and events within big matches are heavily discussed on Twitter. It therefore provides an excellent case study for event detection.
Here we analyse tweets about the FA Cup final, the climax of the English football season, for 2012 and 2013. We evaluate an automated topic detection system using a ground truth derived from mainstream media. We also show that messages can be associated with different teams’ fans, and that they discuss the same events from very different perspectives.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes Twitter users: real-time event detection by social sensors. In: Proc. of WWW 2010, pp. 851–860. ACM (2010)
Bollen, J., Mao, H., Zeng, X.: Twitter mood predicts the stock market. Journal of Computational Science 2(1), 1–8 (2011)
Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Predicting elections with Twitter: What 140 characters reveal about political sentiment. In: Proceedings of 4th ICWSM, vol. 10, pp. 178–185 (2010)
Newman, N.: The rise of social media and its impact on mainstream journalism. Reuters Institute for the Study of Journalism (2009)
FIFA TV: 2010 FIFA World Cup South Africa: Television audience report (2010)
Semiocast: Brazil becomes 2nd country on Twitter, Japan 3rd Netherlands most active country, Paris, France (January 2012)
Twitter: Twitter & TV: Use the power of television to grow your impact, https://business.twitter.com/twitter-tv
Goel, V., Stelter, B.: Social networks in a battle for the second screen. The New York Times (October 2, 2013)
Aiello, L., Petkos, G., Martin, C., Corney, D., Papadopoulos, S., Skraba, R., Goker, A., Kompatsiaris, I., Jaimes, A.: Sensing trending topics in Twitter. IEEE Transactions on Multimedia 15(6), 1268–1282 (2013)
van Oorschot, G., van Erp, M., Dijkshoorn, C.: Automatic extraction of soccer game events from Twitter. In: Proc. of the Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web (2012)
Zhao, S., Zhong, L., Wickramasuriya, J., Vasudevan, V.: Human as real-time sensors of social and physical events: A case study of Twitter and sports games. arXiv preprint arXiv:1106.4300 (2011)
Lanagan, J., Smeaton, A.F.: Using Twitter to detect and tag important events in live sports. In: Artificial Intelligence, pp. 542–545 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Corney, D., Martin, C., Göker, A. (2014). Spot the Ball: Detecting Sports Events on Twitter. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-06028-6_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06027-9
Online ISBN: 978-3-319-06028-6
eBook Packages: Computer ScienceComputer Science (R0)