A combination method of CRF with syntactic rules to identify opinion_holder

Abstract

This paper presents another aspect of sentiment analysis: identifying opinion_holder in the opinionated sentences. To extract opinion_holder, we firstly explore Conditional Random Field(CRF) based on six features including contextual, opinionated_trigger words, POS tags, named entity, dependency and proposed sentence structure feature, and dependency is adjusted to be better helpful for containing contextual dependency information. Then we propose two novel syntactic rules with opinionated_trigger words to directly identify opinion_holder from the parse trees. The results show that the precision from CRF is much higher than that of syntactic rules, while the recall is lower than. So we combine CRF with syntactic rules used as additional three features including HolderNode, ChunkPosition and Paths for the CRF to train our model. The combination results of the system illustrate the higher recall and higher F-measure under the almost same high precision.