Sentence-Level Opinion Analysis by CopeOpi in NTCIR-7

In this paper, we introduce our system, CopeOpi, for analyzing opinionated information in NTCIR-7 MOAT task’s document collections. We participated in all tasks except opinion target extraction and submitted three runs for both simplified and traditional Chinese sides. For opinion extraction task, our algorithm was based on the bag-ofcharacter methods proposed in NTCIR-6 and considered morphological structures of Chinese words to extract opinion words more correctly. How distant an opinion word is to the end of the sentence is also considered to adjust its opinion weight. The performance of the opinion extraction, which is the second best of all participants, achieves the fmeasure 0.672 under the lenient metric and 0.783 under the strict metric. The performances of polarity detection and the relevance judgment are both ranked the third.