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In topic models of the social networks, these are usually some frequent words, such as Barack Obama, and they appear in many different topics. Users usually are interested in these words, so they cannot be removed while analyzing, and this poses a huge challenge for topic analysis. In order to solve this problem, this paper took popularity into consideration while modeling topics. This paper defined the concept of popularity for nodes in the social networks, and proposed an extended topic model containing node popularity. The experiments show that, the proposed model has better prediction ability, and is more effective in prediction accuracy than related works. [ABSTRACT FROM AUTHOR]