Abstract
This paper systematically exploited various lexical features for opinion analysis on blog data using a statistical learning framework. Our experimental results using the TREC Blog track data show that all the features we explored effectively represent opinion expressions, and different classification strategies have a significant impact on opinion classification performance. We also present results when combining opinion analysis with the retrieval component for the task of retrieving relevant and opinionated blogs. Compared with the best results in the TREC evaluation, our system achieves reasonable performance, but does not rely on much human knowledge or deep level linguistic analysis.
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