Abstract
Recently, Social Network Service has made a meteoric rise as means of communication to sharing important information. peoples discuss about social issues, especially in Twitter. Besides, unlike any other social network service, Twitter users can follow without the agreement of the other party, for this reason, the users has followers with various intentions exist. To measure followers’s agree about a followee’s opinion, our method builds issue clusters by defining trust period about extracting an issue. In this paper, we propose two methods for follower classification that are based on extraction of Influential supporters and issues cluster that is reflected on a target user’s opinion. To evaluate the effectiveness of the proposed method, we examine behaviors of followers of politicians from Twitter data. As a result of the experiment, the proposed approach effectively classifies the follower based on issues reflected opinions of the target user and Influential supporters.
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Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2044811).
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Jeong, KY., Seol, JW., Lee, K.S. (2014). Follower Classification Based on User Behavior for Issue Clusters. In: Herawan, T., Deris, M., Abawajy, J. (eds) Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering, vol 285. Springer, Singapore. https://doi.org/10.1007/978-981-4585-18-7_17
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DOI: https://doi.org/10.1007/978-981-4585-18-7_17
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