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Clustering of Weibo users is one of the most important topics in data mining on social network. Clustering can help dig out the relations among people or between people and resources. A lot of work relating to clustering has been done on analyzing personal relationship, whereas we focus our clustering model on preferences and interests. In this article, we propose a new clustering model focusing on users’ tags people choose to describe themselves. First, we will study the characteristics of Sina Weibo tags of users, which are the foundation of the new clustering model. Second, we will use the word2vec tool to cluster Weibo users based on their tags and verify the accuracy of the results.

A New Clustering Model Based on Word2vec Mining on Sina Weibo Users' Tags