Optimizing modularity to identify semantic orientation of Chinese words
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摘要
Inferring the semantic orientation of subjective words (including adjectives, adverbs, nouns, and verbs) is an important task for sentiment analysis of texts. This paper proposes a novel algorithm, which attempts to attack this problem by optimizing the modularity of the word-to-word graph. Experimental results indicate that proposed method has two main advantages: (1) by spectral optimization of modularity, proposed approach displays a higher accuracy than other methods in inferring semantic orientation. For example, it achieves an accuracy of 88.8% on the HowNet-generated test set and (2) by effective usage of the global information, proposed approach is insensitive to the choice of paradigm words. In our experiment, only one pair of paradigm words is needed.
论文关键词:Semantic detection,Opinion mining,Information retrieval
论文评审过程:Available online 28 December 2009.
论文官网地址:https://doi.org/10.1016/j.eswa.2009.12.088