Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-23863-5_8 | KES (2) |
Keywords | Field | DocType |
graph representation,various marketing domain,buzz marketing site,graph structure,method model,text document,consumer behavior analysis,unexpected relationship,time series concept graph,text mining method,flu pandemic,consumer behavior | Air purifiers,Graph,Advertising,Computer science,Consumer behaviour,Pandemic,Marketing buzz,Graph (abstract data type),Concept graph | Conference |
Volume | ISSN | Citations |
6882 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tetsuji Kuboyama | 1 | 140 | 29.36 |
| Takako Hashimoto | 2 | 50 | 18.47 |
| Yukari Shirota | 3 | 1 | 0.36 |