Network analysis of online bidding activity
I. Yang, E. Oh, B. Kahng
Abstract
With the advent of digital media, people are increasingly resorting to online channels for commercial transactions. Online auction is a prototypical example. In such online transactions, the pattern of bidding activity is more complex than traditional online transactions; this is because the number of bidders participating in a given transaction is not bounded and the bidders can also easily respond to the bidding instantaneously. By using the recently developed network theory, we study the interaction patterns between bidders (items) who (that) are connected when they bid for the same item (if the item is bid by the same bidder). The resulting network is analyzed by using the hierarchical clustering algorithm, which is used for clustering analysis for expression data from DNA microarrays. A dendrogram is constructed for the item subcategories; this dendrogram is compared with a traditional classification scheme. The implication of the difference between the two is discussed.
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