Consumer Behavior Analysis from Buzz Marketing Sites over Time Series Concept Graphs

  • Tetsuji Kuboyama
  • Takako Hashimoto
  • Yukari Shirota
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6882)


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.


Consumer Behavior Current Topic Concept Graph Time Series Variation Major Structure Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tetsuji Kuboyama
    • 1
  • Takako Hashimoto
    • 2
  • Yukari Shirota
    • 3
  1. 1.Computer CenterGakushuin UniversityToshimaJapan
  2. 2.Commerce and EconomicsChiba University of CommerceChibaJapan
  3. 3.Faculty of EconomicsGakushuin UniversityToshimaJapan

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