Improved LDA model for microblog topic mining

Abstract

Abstract: With the dramatic increase of Sina microblog users, microblog websites have been the platformsfor a wide spectrum of users to get information. Due to the fact that microblog is a special kind of text with the restricted length, traditional topic models could not be used to analyze the microblog content very well. RT-LDA, a microblog generation model based on LDA is proposed in this paper. Gibbs sampling is chosen to deduce the model, which can not only mine the topics of each microblog accurately but also induce the distribution of the concerned topics. RT-LDA’s effective utility on topic mining of the microblogs is verified by the experiments on real data.

Key words: Sina microblog, text mining, RT-LDA, Gibbs sampling

CLC Number:

TP39

XIE Hao, JIANG Hong. Improved LDA model for microblog topic mining[J]. Journal of East China Normal University(Natural Sc, 2013, 2013(6): 93-101.

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