Sentiment Polarity Analysis based multi-dictionary

This paper presents a novel algorithm for Chinese online reviews, which identifies sentiment polarity. To determine the sentence is negative or positive, we extracted opinion words and identified their opinion targets by CRFs and establish the absolute emotional dictionary (AbED), the relative emotional dictionary (ReED), the field of emotional dictionary (FiED) and the field of targets and opinion words dictionary (TfED). With those emotional dictionary, negative dictionary and modified dictionary, we achieved an effective algorithm to discriminate sentiment polarity by multi-string pattern matching algorithm. For evaluation, we used car online reviews, hotel online reviews and computer online reviews which annotated positive or negative. Experimental results show that our proposed method has made a higher precision and recall rate.