Current work on automatic opinion min- ing has ignored opinion targets expressed by anaphorical pronouns, thereby missing a significant number of opinion targets. In this paper we empirically evaluate whether using an off-the-shelf anaphora resolution algorithm can improve the performance of a baseline opinion mining system. We present an analysis based on two different anaphora resolution systems. Our exper- iments on a movie review corpus demon- strate, that an unsupervised anaphora reso- lution algorithm significantly improves the opinion target extraction. We furthermore suggest domain and task specific exten- sions to an off-the-shelf algorithm which in turn yield significant improvements.

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