Paper: Exploring English Lexicon Knowledge for Chinese Sentiment Analysis

ACL ID W10-4116
Title Exploring English Lexicon Knowledge for Chinese Sentiment Analysis
Venue Joint Conference on Chinese Language Processing
Session Main Conference
Year 2010
Authors

This paper presents a weakly-supervised method for Chinese sentiment analysis by incorporating lexical prior knowledge obtained from English sentiment lexi- cons through machine translation. A mechanism is introduced to incorpo- rate the prior information about polarity- bearing words obtained from existing sentiment lexicons into latent Dirichlet allocation (LDA) where sentiment labels are considered as topics. Experiments on Chinese product reviews on mobile phones, digital cameras, MP3 players, and monitors demonstrate the feasibil- ity and effectiveness of the proposed ap- proach and show that the weakly su- pervised LDA model performs as well as supervised classifiers such as Naive Bayes and Support vector Machines with an average of 83% accuracy achieved over a total of 5484 review d...