FACTUS: faceted twitter user search using twitter lists
WISE'11 Proceedings of the 12th international conference on Web information system engineering
User community reconstruction using sampled microblogging data
Proceedings of the 21st international conference companion on World Wide Web
Effective web video clustering using playlist information
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Examining lists on Twitter to uncover relationships between following, membership and subscription
Proceedings of the 22nd international conference on World Wide Web companion
Measuring and visualizing interest similarity between microblog users
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
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In this paper, we address the problem of tagging users in Twitter, one of the most popular micro-blogging services. There are growing needs to get useful information from Twitter, because an enormous amount of information is transmitted in real time. Twitter users, who play an important role as information sources, typically transmit information about some particular topics which they are interested in. Therefore, to identify useful information, it is very important to know which topics a user tends to transmit. In this paper, we propose a method to discover appropriate topics for a user by using Twitter list. Twitter list is an official functionality to make a"user list, " list members tend to transmit information about the topic represented in the name of the list. From this observation, our idea is to extract tags from list names, and exploit the relationship among lists, tags extracted from the list names, and list members. Experimental results show the effectiveness of the proposed method.