Towards a chinese common and common sense knowledge base for sentiment analysis

Authors:
Erik Cambria;Amir Hussain;Tariq Durrani;Jiajun Zhang
Affiliations:
Temasek Laboratories, National University of Singapore, Singapore;Dept. of Computing Science and Mathematics, University of Stirling, UK;Dept. of Electronic and Electrical Engineering, University of Strathclyde, UK;National Laboratory of Pattern Recognition, Chinese Academy of Sciences, China
Venue:
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Year:
2012

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Abstract

To date, the majority of sentiment analysis research has focused on English language. Recent studies, however, show that non-native English speakers heavily support the growing use of Internet. Chinese, specifically, is poised to outpace English as the dominant language online in a few years' time. So far, just a few isolated research endeavors have been undertaken to meet the demands of real-life Chinese web environments. Natural language processing research endeavor, in fact, primarily depends on the availability of resources like lexicons and corpora, which are still very limited for sentiment analysis research in Chinese language. To this end, we are developing a Chinese common and common sense knowledge base for sentiment analysis by blending the largest existing taxonomy of English common knowledge with a semantic network of English common sense knowledge, and by using machine translation techniques to effectively translate its content into Chinese.