Name
Abstract | ||
|---|---|---|
This paper proposes a method to discover consumer behavior from buzz marketing sites. For example, in 2009, the super-flu virus spawned significant effects on various product marketing domains around the globe. Using text mining technology, we found a relationship between the flu pandemic and the reluctance of consumers to buy digital single-lens reflex camera. We could easily expect more air purifiers to be sold due to flu pandemic. However, the reluctance to buy digital single-lens reflex cameras because of the flu is not something we would have expected. This paper applies text mining techniques to analyze expected and unexpected consumer behavior caused by a current topic like the flu. The unforeseen relationship between a current topic and products is modeled and visualized using a directed graph that shows implicit knowledge. Consumer behavior is further analyzed based on the time series variation of directed graph structures. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.3233/978-1-60750-992-9-259 | Frontiers in Artificial Intelligence and Applications |
Keywords | Field | DocType |
Data mining,marketing research,Web Intelligence,visual analysis | Discrete mathematics,Graph,Advertising,Consumer behaviour,Mathematics,Marketing buzz | Conference |
Volume | ISSN | Citations |
237 | 0922-6389 | 1 |
PageRank | References | Authors |
0.36 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takako Hashimoto | 1 | 50 | 18.47 |
| Tetsuji Kuboyama | 2 | 140 | 29.36 |
| Yukari Shirota | 3 | 1 | 0.36 |