Microblog Hot Topics Discovery Method Based on Probabilistic Topic Model
Mi Wen · Computer Systems and Applications · 2014
Microblog has the characteristic of short length, complex structure and words deformation. Therefore, traditional vector space model(VSM) and latent semantic analysis(LSA) are not suitable for modeling them. In this paper, a two stage clustering algorithm based on probabilistic latent semantic analysis(pLSA) and Kmeans clustering(Kmeans) is proposed. Besides, this paper also presents the definition of popularity and mechanism of sorting the topics. Experiments show that our method can effectively cluster topics and be applied to microblog hot topic detection.