Deep Learning for Chinese Micro-blog Sentiment Analysis
LIANG Jun1, CHAI Yumei1, YUAN Huibin2, ZAN Hongying1, LIU Ming1
1.School of Information Engineering, Zhengzhou University ,Zhengzhou Henan, 450001, China;
2. China Institute of Nuclear Information & Economics, Beijing 100048, China
Abstract：Chinese micro-blog sentiment analysis aims to discover the user attitude towards hot events. Most of the current studies analyze the micro-blog sentiment by traditional algorithms such as SVM, CRF based on hand-engineered features. This paper explores the feasibility of performing Chinese micro-blog sentiment analysis by deep learning. We try to avoid task-specific features, and use recursive neural networks to discover relevant features to the tasks. We propose a novel model - sentiment polarity transition model - based on the relationship between neighboring words of a sentence to strengthen the text association. The proposed method achieves a performance close to state-of-the-art methods based on the hand-engineered features, but saving a lot of manual annotation work.
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2014, Vol. 28 
