Abstract
This article focuses on understanding users' interests in European cities based on log file analysis of keywords entered by users on www.visiteuropeancities.info. It applies various text analysis steps in order to extract significant patterns from the queries made by the users. Multidimensional scaling (MDS) is used for constructing a map of similarities based on the unaided responses gained from the users' information requests. Multiple regression analysis between the most frequently used terms entered by the users and the geometrical representation generated by the MDS provides additional insights in the semantics defining competitive differences between 32 city break destinations in Europe. Findings comprise information on cities that can be considered as kindred in regard to the information demanded by the users of the Web portal. As it becomes clear in which areas cities are perceived as similar, this findings can be used by city (tourism) managers in order to revise their communication plan regarding their own city if desired.
| Original language | English |
|---|---|
| Pages (from-to) | 119-131 |
| Number of pages | 13 |
| Journal | Journal of Information Technology & Tourism |
| Volume | 10 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Jun 2008 |
Keywords
- City Tourism
- Domain-specific search portal
- log file analysis
- Multi-dimensional scaling
- web usage mining