Yoosin Kim, Sung-Gwan Hong, Hee-Joo Kang, Seung-Ryul Jeong, Journal of Internet Computing and Services, Vol. 18, No. 4, pp. 121-0, Aug. 2017
10.7472/jksii.2017.18.4.121, Full Text:
Keywords: e-Consumer Sentiment Index, Text Mining, Ontology, sentiment analysis

Abstract

With emergence of Internet, social media, and mobile service, the consumers have actively presented their opinions and sentiment, and then it is spreading out real time as well. The user-generated text data on the Internet and social media is not only the communication text among the users but also the valuable resource to be analyzed for knowing the users' intent and sentiment. In special, economic participants have strongly asked that the social big data and its' analytics supports to recognize and forecast the economic trend in future. In this regard, the governments and the businesses are trying to apply the social big data into making the social and economic solutions. Therefore, this study aims to reveal the capability of social big data analysis for the economic use. The research proposed a social big data analysis model and an online consumer sentiment index. To test the model and index, the researchers developed an economic survey ontology, defined a sentiment dictionary for sentiment analysis, conducted classification and sentiment analysis, and calculated the online consumer sentiment index. In addition, the online consumer sentiment index was compared and validated with the composite consumer survey index of the Bank of Korea.

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