Warning system for online market research – Identifying critical situations in online opinion formation |
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| Authors: | Carolin Kaiser Sabine Schlick Freimut Bodendorf |
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| Affiliation: | 1. Department of Automation Science and Technology, School of Electronic and Information Engineering, Xi''an Jiaotong University, No.28 Xianning West Road, Xi''an, Shaanxi 710049, China;2. School of Information Science and Technology, Northwest University, Xi''an, China;1. Australian Research Centre in Sex, Health and Society, La Trobe University, Melbourne, Australia;2. School of Social Sciences, University of NSW, Sydney, Australia;3. Centre For Social Research in Health, University of NSW, Australia, Sydney;4. UQ Centre for Clinical Research, The University of Queensland, Brisbane, Australia;5. The Peter Doherty Institute for Infection and Immunity, University of Melbourne and Royal Melbourne Hospital, Melbourne, Australia;6. Department of Infectious Diseases, Alfred Health and Monash University, Melbourne, Australia;7. UNC Project-China, University of North Carolina, Guangzhou, China;8. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;9. Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, USA;10. Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA;11. Centre for Health Communication and Participation, School of Psychology and Public Health, La Trobe University, Melbourne;1. Department of Marketing, College of Management, Mahidol University, 69 Vipawadee Rangsit Road, Samsennai, Phayathai, Bangkok, Thailand 10400;2. Department of Marketing, Eli Broad Graduate School of Business, Michigan State University, N307 Business Complex, 632 Bogue Street, East Lansing, MI48824-1122, United States;3. Department of Marketing, Eli Broad Graduate School of Business, Michigan State University, N304 Business Complex, 632 Bogue Street, East Lansing, MI 48823 1122, United States |
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| Abstract: | More and more consumers are relying on online opinions when making purchasing decisions. For this reason, companies must have knowledge of the actual standing of their products on the Web. A warning system for online market research is being proposed which allows the identification of critical situations in online opinion formation. When critical situations are detected, warnings are subsequently sent to marketing managers and thus allowing marketers the ability to initiate preventive measures. The warning system operates on a knowledge base which contains product-related success values, online opinions and patterns of social interactions. This knowledge is acquired using methods coming from information extraction, text mining and social network analysis. Based on this knowledge the warning system judges situations accordingly. For this purpose, a neuro-fuzzy approach is chosen which learns linguistic rules from data. These rules are employed to estimate future situations. The warning system is applied to two scenarios and yields good results. An evaluation shows that all components of the warning system outperform alternative methods. |
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