Modeling the Product Space as a Network

In the market basket setting, we are given a series of transactions each composed of one or more items and the goal is to find relationships between items, usually sets of items that tend to occur in the same transaction. Association rules, a popular approach for mining such data, are limited in the ability to express complex interactions between items. Our work defines some of these limitations and addresses them by modeling the set of transactions as a network. We develop both a general methodology for analyzing networks of products, and a privacy-preserving protocol such that product network information can be securely shared among stores. In general, our network based view of transactional data is able to infer relationships that are more expressive and expansive than those produced by a typical association rules analysis

Ad-sponsored Business Models and Compatibility Incentives of Social Networks

This paper examines social networks' incentives to establish compatibility under fee and ad-sponsored business models. I analyze the competition between two social networks and show that compatibility is only possible when the two networks are ad-sponsored. I also find that even when both networks are ad-sponsored, a network with a significant installed-base advantage may choose not to be compatible when the cost from sharing the market outweighs the benefit from additional ad profits. Finally, compatibility also requires a significant number of single-homing users. The results are consistent with empirical observations of social networks and suggest that increased adoption of ad-sponsored business models may lead to many de-facto standards in high-technology industries