Microblog Topic Mining Based on FR-DATM

作者：Liu Bingyu^*; Wang Cuirong; Wang Yiran; Zhang Kun; Wang Cong

来源：Chinese Journal of Electronics, 2018, 27(2): 334-341.

DOI：10.1049/cje.2017.12.006

• Topic mining
• Microblog
• Dynamic latend topic model
• Author topic model

Microblog has become a major platform for people to release or obtain information. Texts on Microblog are shorter and have scarce co-occurrence information of terms. It is more complicated to discover topics from Microblog. To solve the problems, this paper proposes a dynamic author topic model FR-DATM and uses Gibbs sampling implementation for inference of this model. The FR-DATM model analyzes the relationships between blogs, and connects the related blogs to solve the sparseness of data. It allows blogs to be related to multiple topics, and each author of the blogs is also related to the topics of the blogs. The FR-DATM can also mine the topic evolution of the blogs and the authors. Experiments on Twitter dataset show that FR-DATM outperforms Latent dirichlet allocation (LDA) model and Microblog latent Dirichlet Allocation (MB-LDA) from three different perspectives: The quality of generated latent topics, the model perplexity and FR-DATM can mine the topic that the author are concerned dynamically.

• 出版日期2018-3
• 单位东北大学