Tagging users based on Twitter lists. (1st January 2012) - Yamaguchi, Yuto; Amagasa, Toshiyuki; Kitagawa, Hiroyuki
This paper addresses the problem of tagging users in Twitter, one of the most popular microblogs. Although there are an enormous number of Twitter users, some are particularly influential regarding certain topics (e.g., politics, sports). These users often transmit useful information about their topics. For example, a user familiar with political issues often transmits useful information about the latest political news. To obtain useful information, therefore, it is very important to know these user topics. To discover user topics, we propose a user tagging method using Twitter lists, the official Twitter function for making and sharing user lists. From our observations, users included in the same list were likely to have posted on the same topic. This topic was often described by the list name. For example, the list named 'politicians-list' has politicians as its members. For this reason, our proposed method regards list names as sequences of tags and assigns them to list members. Experiments conducted using two datasets showed that our proposed method works effectively in the user profiling domain and the user ranking domain.