dorsal/arxiv
View SchemaeBay users form stable groups of common interest
| Authors | Joerg Reichardt, Stefan Bornholdt |
|---|---|
| Categories | |
| ArXiv ID | physics/0503138 |
| URL | https://arxiv.org/abs/physics/0503138 |
| DOI | 10.1088/1742-5468/2007/06/P06016 |
| Journal | J. Stat. Mech. (2007) P06016 |
Abstract
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.
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"abstract": "Market segmentation of an online auction site is studied by analyzing the\nusers\u0027 bidding behavior. The distribution of user activity is investigated and\na network of bidders connected by common interest in individual articles is\nconstructed. The network\u0027s cluster structure corresponds to the main user\ngroups according to common interest, exhibiting hierarchy and overlap. Key\nfeature of the analysis is its independence of any similarity measure between\nthe articles offered on eBay, as such a measure would only introduce bias in\nthe analysis. Results are compared to null models based on random networks and\nclusters are validated and interpreted using the taxonomic classifications of\neBay categories. We find clear-cut and coherent interest profiles for the\nbidders in each cluster. The interest profiles of bidder groups are compared to\nthe classification of articles actually bought by these users during the time\nspan 6-9 months after the initial grouping. The interest profiles discovered\nremain stable, indicating typical interest profiles in society. Our results\nshow how network theory can be applied successfully to problems of market\nsegmentation and sociological milieu studies with sparse, high dimensional\ndata.",
"arxiv_id": "physics/0503138",
"authors": [
"Joerg Reichardt",
"Stefan Bornholdt"
],
"categories": [
"physics.soc-ph",
"cond-mat.stat-mech"
],
"doi": "10.1088/1742-5468/2007/06/P06016",
"journal_ref": "J. Stat. Mech. (2007) P06016",
"title": "eBay users form stable groups of common interest",
"url": "https://arxiv.org/abs/physics/0503138"
},
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