NDLI: Microblog Topic Mining Based on FR-DATM

Content Provider	IET Digital Library
Author	U, Bingyu L I G, Cuirong W A N G, Yiran W A N G, Kun Z H A N G, Cong W A N
Abstract	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.
Starting Page	334
Ending Page	341
Page Count	8
ISSN	10224653
Volume Number	27
e-ISSN	20755597
Issue Number	Issue 2, Mar (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/27/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2017.12.006
Journal	Chinese Journal of Electronics
Publisher Date	2018-03-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	Data Handling Technique Data Mining Dynamic Author Topic Model FR-DATM FR-DATM Model Analyzes The Relationships Generated Latent Topics Information Network Knowledge Engineering Technique Latent Dirichlet Allocation Model Microblog Latent Dirichlet Allocation Microblog Topic Mining Multiple Topics Related Blogs Scarce Co-occurrence Information Social Networking (online) Statistics Text Analysis Topic Evolution Web Site
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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