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《Journal of Data Acquisition and Processing》 2015-01
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Semantic Orientation Identification for Terms From Chinese Micro-blogs Based on Word Affinity Measure

Tang Haohao;Wang Bo;Zhou Jie;Chen Dong;Liu Shaoyu;Institute of Information and System Engineering,PLA Information Engineering University;  
How to identify the semantic orientation of terms and build a high-quality sentiment dictionary to improve the accuracy of sentiment analysis on Micro-blogs has significant importance.Traditional algorithms based on corpus are sensitive to the seed words,and cannot effectively identify semantic orientation identification on low-frequency terms.To solve this problem,an algorithm based on word affinity measure is proposed to identify the semantic orientation of terms from Chinese Micro-blogs.Firstly,candidate words are extracted by the part of speech combination patterns.Secondly,Micro-blog emoticons are selected as seed words,and word affinity networks are built.Then,low-frequency words are expanded by a synonyms dictionary during calculating the semantic orientation similarity between candidate words and seed words.Finally,the semantic orientation is determined according to the threshold.Experiments are conducted on a corpus with two million Micro-blogs using the proposed algorithm and traditional algorithms respectively.Experimental results show the advantage of the proposed algorithm.
【Fund】: 国家高技术研究发展计划(“八六三”计划)(2011AA7032030D)资助项目;; 全军军事研究生课题(2011JY002-158)资助项目
【CateGory Index】: TP391.1
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