Abstract
This paper proposes a text mining method for detecting drastic changes of consumer behavior over time from buzz marketing sites, and applies it to finding the effects of the flu pandemic on consumer behavior in various marketing domains. It is expected that more air purifiers are sold due to the pandemic, and it is, actually, observed. By using our method, we reveal an unexpected relationship between the flu pandemic and the reluctance of consumers to buy digital single-lens reflex camera. Our method models and visualizes the relationship between a current topic and products using a graph representation of knowledge generated from the text documents in a buzz marketing site. The change of consumer behavior is detected by quantifying the difference of the graph structures over time.
This work is partially supported by Grand-in-Aid for Scientific Research 23500185 from the Ministry of Education, Culture, Sports, Science and Technology, Japan.
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Kuboyama, T., Hashimoto, T., Shirota, Y. (2011). Consumer Behavior Analysis from Buzz Marketing Sites over Time Series Concept Graphs. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23863-5_8
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DOI: https://doi.org/10.1007/978-3-642-23863-5_8
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