¹College of automation, Harbin Engineering University, Harbin 150001, Heilongjiang, China
²College of Science, Harbin Engineering University, Harbin 150001, Heilongjiang, China
³College of electronic engineering, Naval University of Engineering, Wuhan 430033, Hubei, China

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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.

Index Terms—Sentiment analysis, microblogger, text chain

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Cite: Lina Liu, Jihong Shen, Qianghua Zhu, "Detecting Microblogger’s Attitude towards Bursty Events: a Text Chain Model," Journal of Software vol. 9, no. 5, pp. 1163-1169, 2014.