Analysis of Product Purchase Patterns in a Co-Purchase Network

Real world social networks are often temporal in nature. They evolve with time as new nodes may appear, old nodes may cease to exist and the relationships between the entities may also change. In this paper, we have studied a publicly available dynamic network dataset, namely Amazon co-purchase network dataset. We have analyzed the network data to understand the significance of nodes with high in-degree and high out-degree. We subsequently analyze the evolution of communities in the network by observing the change of association among nodes and by observing communities to see how many members they could retain over time. We show some frequent item sets from the co-purchase market basket in terms of the item categories and subcategories. We finally select some central entities and group of such entities from the network to recommend how promoting some of the co-purchased items may increase the sales of the selected items.