Account matching across heterogeneous networks

Due to the development of web services, many social network sites, as well as online shopping sites have been booming in the past decade, where it is a common phenomenon that people are likely to use multiple services at the same time. Discovering the correspondence between accounts of a same individual is a crucial prerequisite for many interesting cross network applications, such as improving the recommendation performance of the online shopping sites by using extra information from social network services. In this paper, we propose a gametheoretic method to identify correlation accounts of individuals between social network sites and online shopping sites with stable matching model, incorporating accounts profiles as well as historical behaviors. The results show that our method identifies up to 70% of correlation accounts between Facebook and eBay, one of the most popular social network sites and online shopping sites in the world, respectively.