Conference Proceeding Article
Twitter network is currently overwhelmed by massive amount of tweets generated by its users. To effectively organize and search tweets, users have to depend on appropriate hashtags inserted into tweets. We begin our research on hashtags by first analyzing a Twitter dataset generated by more than 150,000 Singapore users over a three-month period. Among several interesting findings about hashtag usage by this user community, we have found a consistent and significant use of new hashtags on a daily basis. This suggests that most hashtags have very short life span. We further propose a novel hashtag recommendation method based on collaborative filtering and the method recommends hashtags found in the previous month's data. Our method considers both user preferences and tweet content in selecting hashtags to be recommended. Our experiments show that our method yields better performance than recommendation based only on tweet content, even by considering the hashtags adopted by a small number (1 to 3)of users who share similar user preferences.
Twitter, hashtag, recommendation systems
Communication Technology and New Media | Databases and Information Systems | Social Media
Data Management and Analytics
Social Informatics: 4th International Conference, SocInfo 2012, Lausanne, Switzerland, December 5-7, 2012. Proceedings
City or Country
KYWE, Su Mon; HOANG, Tuan-Anh; LIM, Ee Peng; and ZHU, Feida.
On Recommending Hashtags in Twitter Networks. (2012). Social Informatics: 4th International Conference, SocInfo 2012, Lausanne, Switzerland, December 5-7, 2012. Proceedings. 7710, 337-350. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1697
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