Paper: Improving Blog Polarity Classification via Topic Analysis and Adaptive Methods

ACL ID N10-1042
Title Improving Blog Polarity Classification via Topic Analysis and Adaptive Methods
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

In this paper we examine different linguistic features for sentimental polarity classification, and perform a comparative study on this task between blog and re- view data. We found that results on blog are much worse than reviews and investigated two methods to improve the performance on blogs. First we ex- plored information retrieval based topic analysis to extract relevant sentences to the given topics for po- larity classification. Second, we adopted an adaptive method where we train classifiers from review data and incorporate their hypothesis as features. Both methods yielded performance gain for polarity clas- sification on blog data.