Earticle

초록

영어

These days, emerging social media such as blogospheres, online communities, and social networking sites, enables researchers to discover market intelligence and business insight by analyzing online behaviors. Specifically, firms constantly require approach to research consumers’ opinions and to identify competitive advantage in the competing market. Analyzing and comparing consumers’ opinions and sentiment toward rivals in the same industry can help business decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis and opinion mining in social media through a multiple case study: two popular and competing instant noodles in the Korean instant noodle industry: a market leader and a market follower. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages between January and September, 2012 year, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed opinion mining to present consumers’ sentiment and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the opinion mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

목차

ABSTRACT
 1. INTRODUCTION
 2. RELATED WORK
 3. PROPOSED APPROACH
 4. SENIMENT ANALASY RESULTS
 5. STATISTICAL ANALYSIS RESULTS
 6. DISCUSSION AND IMPLICATIONS
 7. CONCLUSION AND FUTURE RESEARCH
 REFERENCES

저자

• Yoosin Kim [ Department of MIS, Chungbuk National University, Cheongju, Korea ]
• Mingon Kang [ Department of Computer Science & Information Systems, Texas A&M University-Commerce, TX, U.S.A. ]
• Seung Ryul Jeong [ Business IT Graduate School, Kookmin University, Seoul, South Korea ] Corresponding Author

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