Matching User Proﬁles Across Social Networks Nacéra Bennacer 1 , Coriane Nana Jipmo 1 , Antonio Penta 2 , and Gianluca Quercini 1 1 Supélec E3S, 3, rue Joliot-Curie, 91190 Gif-sur-Yvette (France) {nacera.bennacer,coriane.nanajipmo,gianluca.quercini}@supelec.fr 2 Università di Torino Corso Svizzera 185, Torino (Italy) penta@di.unito.it 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 pro- ﬁles in several social networks, each containing partially overlapping sets of personal information. Matching those diﬀerent proﬁles allows to cre- ate 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, ob- tained on a real dataset composed of around 2 million proﬁles, show that our algorithm achieves a high accuracy. 1 Introduction A social network is a set of individuals and their relationships. In a broader sense, the term social network also refers to a website, such as Facebook and LinkedIn, which enables individuals to create a personal page, or proﬁle, and to stay in contact with their acquaintances. 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 on their proﬁles some personal information, such as their names, family names, locations and birth dates, just to name a few. Several surveys showed that Social Networking Services (SNSs) users tend to share many of their personal data, including sensitive information, such as home addresses and phone numbers [1–3]. However, it is not uncommon that an individual creates multiple proﬁles in diﬀerent SNSs, each disclosing sets of personal information that are unlikely to be identical, though they might overlap. Indeed, proﬁle information might not be M. Jarke et al. (Eds.): CAiSE 2014, LNCS 8484, pp. 424–438, 2014. c  Springer International Publishing Switzerland 2014