doi: 10.4304/jsw.9.5.1163-1169
Detecting Microblogger’s Attitude towards Bursty Events: a Text Chain Model
- 1 College of automation, Harbin Engineering University, Harbin 150001, Heilongjiang, China
- 2 College of Science, Harbin Engineering University, Harbin 150001, Heilongjiang, China
- 3 College of electronic engineering, Naval University of Engineering, Wuhan 430033, Hubei, China
Abstract
With the booming of social media, microblog attracts more and more people to discuss public issues and share their views and opinions. In this paper, we focus on the sentiment analysis in Chinese microblog from the aspect of users. We aim to detect microbloger’s attitude on bursty events by proposing a novel text chain model. We firstly formulate the problem of user sentiment analysis. By leveraging the link symbols in contents, we generate micrblog units and prune to user text chains which will be regarded as a whole in the follow-up process. Then, we use MaxEnt-LDA model to extract target events and opinion words, and use a lexicon-based model to detect user’s orientation towards a certain atomistic event. Experimental results show that our model could detect user’s attitudes effectively.
Keywords
- Sentiment analysis
- microblogger
- text c
How to Cite
Lina Liu, Jihong Shen, and Qianghua Zhu, "Detecting Microblogger’s Attitude towards Bursty Events: a Text Chain Model," Journal of Software, vol. 9, no. 5, pp. 1163-1169, 2014. https://doi.org/ 10.4304/jsw.9.5.1163-1169
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).