智能系统学报2017，Vol.12Issue(5)：645-652,8.DOI:10.11992/tis.201312032
一种基于OCC模型的文本情感挖掘方法
OCC-model-based text-emotion mining method
摘要
Abstract
Opinion mining, also called sentiment analysis, as one of the core research areas in the network-oriented social media analysis and mining domain, has important practical and research significance. Due to the weaknesses and limitations of traditional opinion mining methods, in this study, we designe and implemente an OCC emotion model-based opinion mining method for extracting emotion types from text. First, we adopte a statistical method to construct an emotion dictionary, based on candidate sets collected by the WordNet dictionary, as well as several syntactic dependent relationships and a small amount of annotated data. Next, we refine the constructed emotion-dimension dictionary to improve its quality by filtering out non-emotional words as well as emotional words that have conflicting syntactic or orientation. Lastly, we generate six main emotion types based on the obtained emotion-dimension dictionary combined with the corresponding relations between emotional dimensions and the different emotion types identified by the OCC model. Experimental results show that the proposed method has obvious advantages with respect to flexibility of usage, interpretability, and effectiveness.关键词
观点挖掘/OCC情感模型/情感维度/情感类型/情感词典/认知心理学/情感挖掘/共现Key words
opinion mining/OCC emotion model/emotional dimension/emotion types/emotion dictionary/cognitive psychology/emotion mining/co-occurrence分类
信息技术与安全科学引用本文复制引用
皇甫璐雯,毛文吉..一种基于OCC模型的文本情感挖掘方法[J].智能系统学报,2017,12(5):645-652,8.基金项目
国家自然科学基金项目(61175040,71025001). （61175040,71025001）
