Chinese Evaluative Information Analysis

Together with the ever-growing amount of Chinese web data, the number of opinions voiced by Chinese users is rapidly increasing, and analyzing them is an important task. This paper introduces a Chinese Evaluative Information Analyzer (CEIA) and proposes a method to improve its performance. We use evaluative information as a unifying term for the information about attitudes, opinions, sentiments and so on. This paper makes three contributions: (i) CEIA can identify and analyze a more diverse and richer set of evaluative information than previous studies for Chinese; (ii) to implement the system, we constructed an original annotated corpus for Chinese evaluative information and built a large sentiment dictionary; (iii) we introduce syntactic dependency, semantic class and distance features to improve the evaluative information extraction. The performance of the system and the effectiveness of the newly introduced features are evaluated in a series of experiments on our Chinese evaluative information corpus. Title and Abstract in Chinese dddddddd dddddddddddddddddddddddddddddddddddd ddddddddddddddddddddddddddddddddddddddd dddddddddCEIAddddddddddddddddddddddddddd dddddddddddddddddddddddddddddddddddddd dddddidddddddddCEIAdddddddddddddddddddddd dddiidddddCEIAdddddddddddddddddddddddddddd dddddiiiddddddddddddddddddddddddddddddddd ddddddddddddddddddddddddddddddddddddddd dddddd