Matching user profiles across social networks

Abstract

Social Networking Sites, such as Facebook and Linkedin, are clear examples of the impact that the Web 2.0 has on people around the world, because they target an aspect of life that is extremely important to anyone: social relationships. The key to building a social network is the ability of finding people that we know in real life, which, in turn, requires those people to make publicly available some personal information, such as their names, family names, locations and birth dates, just to name a few. However, it is not uncommon that individuals create multiple profiles in several social networks, each containing partially overlapping sets of personal information. Matching those different profiles allows to create a global profile that gives a holistic view of the information of an individual. In this paper, we present an algorithm that uses the network topology and the publicly available personal information to iteratively match profiles across n social networks, based on those individuals who disclose the links to their multiple profiles. The evaluation results, obtained on a real dataset composed of around 2 million profiles, show that our algorithm achieves a high accuracy. © 2014 Springer International Publishing.