Abstract
We propose a mutual information approach to identify feature-based opinion expressions in customer reviews. Associations between opinion words and product feature categories are built by this approach. With the association set, we can identify what product feature a review unit refers to, even in the condition without explicit appearance of feature words. It can also be used to judge the semantic relatedness between a feature word and opinion words in its context. Thus it helps to decide which opinion word should contribute its polarity to the review feature. We also introduce the construction of a polarity lexicon, which is applied to identify opinion expressions in reviews. Using the approach proposed in this paper, we supply the polarity lexicon with the related product feature information. With the resource, we can get a better opinion mining result for a product review from different feature aspects.
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