Explaining the Power-Law Degree Distribution in a Social Commerce Network

Social Networks, Vol. 31, No. 4, pp. 262-270, 2009

9 Pages Posted: 1 Jul 2008 Last revised: 4 Aug 2014

See all articles by Andrew T. Stephen

Andrew T. Stephen

University of Oxford - Said Business School

Olivier Toubia

Columbia Business School - Marketing

Date Written: September 8, 2009

Abstract

Social commerce is an emerging trend in which online shops create referral hyperlinks to other shops in the same online marketplace. We study the evolution of a social commerce network in a large online marketplace. Our dataset starts before the birth of the network (at which points shops were not linked to each other) and includes the birth of the network. The network under study exhibits a typical power-law degree distribution. We empirically compare a set of edge formation mechanisms (including preferential attachment and triadic closure) that may explain the emergence of this property. Our results suggest that the evolution of the network and the emergence of its power-law degree distribution are better explained by a network evolution mechanism that relies on vertex attributes that are not based on the structure of the network. Specifically, our analysis suggests that the power-law degree distribution emerges because shops prefer to connect to shops with more diverse assortments, and assortment diversity follows a power-law distribution. Shops with more diverse assortments are more attractive to link to because they are more likely to bring traffic from consumers browsing the WWW. Therefore, our results also imply that social commerce networks should not be studied in isolation, but rather in the context of the broader network in which they are embedded (the WWW).

Keywords: network evolution, social networks, mixture model, social commerce, empirical statistical modeling

JEL Classification: C20, C29, D71, M31

Suggested Citation

Stephen, Andrew T. and Toubia, Olivier, Explaining the Power-Law Degree Distribution in a Social Commerce Network (September 8, 2009). Social Networks, Vol. 31, No. 4, pp. 262-270, 2009. Available at SSRN: https://ssrn.com/abstract=1153113 or http://dx.doi.org/10.2139/ssrn.1153113

Andrew T. Stephen (Contact Author)

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

Olivier Toubia

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

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