Detecting Domain Dedicated Polar Words

There are many examples in which a word changes its polarity from domain to domain. For example, unpredictable is positive in the movie domain, but negative in the product domain. Such words cannot be entered in a “universal sentiment lexicon” which is supposed to be a repository of words with polarity invariant across domains. Rather, we need to maintain separate domain specific sentiment lexicons. The main contribution of this paper is to present an effective method of generating a domain specific sentiment lexicon. For a word whose domain specific polarity needs to be determined, the approach uses the Chi-Square test to detect if the difference is significant between the counts of the word in positive and negative polarity documents. We extract 274 words that are polar in the movie domain, but are not present in the universal sentiment lexicon. Our overall accuracy is around 60% in detecting movie domain specific polar words.