Abstract
Sports spoilers on SNS services such as Twitter, Facebook and so on spoil viewers’ enjoyment when watching recorded matches. To avoid spoilers, people sometimes stay away from SNSs. However, people often use SNSs to habitually check messages posted by their friends and build and maintain their relationships. Therefore, we need an automatic method for detecting spoilers from SNSs. In this paper, we generated a Japanese spoiler dataset on Twitter and investigated the characteristics of the spoilers to create a foothold in construction of automatic spoiler detection system. Consequently, we clarified the relationship between spoilers and the statuses of football matches. In addition, we compared three methods for detecting spoilers and show the usefulness of SVM with Status of Match method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nakamura, S., Tanaka, K.: Temporal filtering system for reducing the risk of spoiling a user’s enjoyment. In: Proceedings of the 12th International Conference on Intelligent User Interfaces, pp. 345–348. ACM, Honolulu (2007)
Leavitt, J.D., Christenfeld, N.J.S.: Story spoilers don’t spoil stories. Psychol. Sci. 22, 1152–1154 (2011)
Rosenbaum, J.E., Johnson, Benjamin, K.: Who’s afraid of spoilers? Need for cognition, need for affect, and narrative selection and enjoyment. Psychol. Pop. Med. Cult. 5, 273–289 (2016)
Ikeda, K., Hijikata, Y., Nishida, S.: Proposal of deleting plots from the reviews to the items with stories. In: Proceedings of SNSMW 2010, vol. 6193, pp. 346–352. CDROM (2010)
Pang, B., Lee, L.: A Sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts. In: Proceedings of ACL 2004, pp. 271–278 (2004)
Boyd-Graber, J., Glasgow, K., Zajac, J.S.: Spoiler alert: machine learning approaches to detect social media posts with revelatory information. In: Proceedings of the 76th Annual Meeting of the American Society for Information Science and Technology, vol. 50, pp. 1–9. ASIST (2013)
Jeon, S., Kim, S., Yu, H.: Spoiler detection in TV program tweets. Inf. Sci. 329, 220–235 (2016)
Top 10 Most Watched Sports In The World. http://top-10-list.org/2010/10/04/10-most-watched-world-sports/. Accessed 27 Jan 2017
Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval: The Concepts and Technology Behind Search, 2nd edn. Addison-Wesley Professional, Boston (2011)
Brody, S., Diakopoulos, N.: Cooooooooooooooollllllllllllll!!!!!!!!!!!!!!: using word lengthening to detect sentiment in microblogs. In: Proceedings of Conference on Empirical Methods in Natural Language Processing, pp. 562–570. Association for Computational Linguistics, Stroudsburg (2011)
Manning, C.D., Schtze, H.: Foundations of Statistical Natural Language Processing. The MIT Press, Cambridge (1999)
Acknowledgments
This work was supported in part by JST ACCEL Grant Number JPMJAC1602, Japan.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Shiratori, Y., Maki, Y., Nakamura, S., Komatsu, T. (2018). Detection of Football Spoilers on Twitter. In: Egi, H., Yuizono, T., Baloian, N., Yoshino, T., Ichimura, S., Rodrigues, A. (eds) Collaboration Technologies and Social Computing. CollabTech 2018. Lecture Notes in Computer Science(), vol 11000. Springer, Cham. https://doi.org/10.1007/978-3-319-98743-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-98743-9_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98742-2
Online ISBN: 978-3-319-98743-9
eBook Packages: Computer ScienceComputer Science (R0)