Extraction of unexpected rules from Twitter hashtags and its application to sports events

Adedoyin-Olowe, Mariam and Gaber, Mohamed Medhat and Dancausa, Carlos and Stahl, Frederic (2014) Extraction of unexpected rules from Twitter hashtags and its application to sports events. In: Proceedings of 13th International Conference on Machine Learning and Applications. IEEE, pp. 207-212.

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Abstract

Twitter has become a dependable microblogging tool for real time information dissemination and newsworthy events broadcast. Its users sometimes break news on the network faster than traditional newsagents due to their presence at ongoing real life events at most times. Different topic detection methods are currently used to match Twitter posts to real life news of mainstream media. In this paper, we analyse tweets relating to the English FA Cup finals 2012 by applying our novel method named TRCM to extract association rules present in hash tag keywords of tweets in different time-slots. Our system identify evolving hash tag keywords with strong association rules in each time-slot. We then map the identified hash tag keywords to event highlights of the game as reported in the ground truth of the main stream media. The performance effectiveness measure of our experiments show that our method perform well as a Topic Detection and Tracking approach.

Item Type: Book Section
Uncontrolled Keywords: Twitter, Association rules, Games, Fans, Pattern matching, Educational institutions
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Enterprise Systems
UoA Collections > UoA11: Computer Science and Informatics
Depositing User: $ Ian McDonald
Date Deposited: 03 Oct 2017 12:02
Last Modified: 03 Oct 2017 12:02
URI: http://www.open-access.bcu.ac.uk/id/eprint/5206

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