Summarizing Microblogging Users with Existing Well-defined Hashtags

The rapid increasing popularity of microblogging has made it an important information seeking platform, and the typical way for a user to get useful information is by following those whose tweet content can draw interest. However, it is not practical to read all the tweets in order to decide whether to follow a user or not. Therefore, a brief and effective user description method is required, which is the focus of this paper. We design a model to automatically detect the most representative hashtags of a microblogging user, with which s/he can be easily known by others. The experimental results on Sina-Weibo, one of the most popular micro-blogging sites in China, show that our model can achieve a better performance than several baseline methods.

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