Detection of Football Spoilers on Twitter
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.
KeywordsBlocking spoilers Machine learning Sports Football SNS Twitter
This work was supported in part by JST ACCEL Grant Number JPMJAC1602, Japan.
- 1.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)Google Scholar
- 3.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)Google Scholar
- 4.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)Google Scholar
- 5.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)Google Scholar
- 6.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)Google Scholar
- 8.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
- 9.Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval: The Concepts and Technology Behind Search, 2nd edn. Addison-Wesley Professional, Boston (2011)Google Scholar
- 10.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)Google Scholar
- 11.Manning, C.D., Schtze, H.: Foundations of Statistical Natural Language Processing. The MIT Press, Cambridge (1999)Google Scholar