1 research outputs found
eBay users form stable groups of common interest
Market segmentation of an online auction site is studied by analyzing the
users' bidding behavior. The distribution of user activity is investigated and
a network of bidders connected by common interest in individual articles is
constructed. The network's cluster structure corresponds to the main user
groups according to common interest, exhibiting hierarchy and overlap. Key
feature of the analysis is its independence of any similarity measure between
the articles offered on eBay, as such a measure would only introduce bias in
the analysis. Results are compared to null models based on random networks and
clusters are validated and interpreted using the taxonomic classifications of
eBay categories. We find clear-cut and coherent interest profiles for the
bidders in each cluster. The interest profiles of bidder groups are compared to
the classification of articles actually bought by these users during the time
span 6-9 months after the initial grouping. The interest profiles discovered
remain stable, indicating typical interest profiles in society. Our results
show how network theory can be applied successfully to problems of market
segmentation and sociological milieu studies with sparse, high dimensional
data.Comment: Major revision of the manuscript. Methodological improvements and
inclusion of analysis of temporal development of user interests. 19 pages, 12
figures, 5 table