Analysis of E-Commerce Product Graphs
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Consumer behavior in retail stores gives rise to product graphs based on copurchasing
or co-viewing behavior. These product graphs can be analyzed using
the known methods of graph analysis. In this paper, we analyze the product graph
at Target Corporation based on the Erd˝os-Renyi random graph model. In particular,
we compute clustering coefficients of actual and random graphs, and we find that
the clustering coefficients of actual graphs are much higher than random graphs.
We conduct the analysis on the entire set of products and also on a per category
basis and find interesting results. We also compute the degree distribution and
we find that the degree distribution is a power law as expected from real world
networks, contrasting with the ER random graph.