User Identification across Social Networks using the Web Profile and Friend Network
Jan Vosecky, Danfeng Hong, Vincent Y. Shen · Int. J. Web Appl. · 2010
Today, it is common that people are users of more than one social network and their friends may also be reg- istered on multiple websites. A facility to aggregate our online friends into a single integrated environment would enable us to keep up-to-date with our virtual contacts more easily, as well as to provide improved facility to search for users across different websites. In this paper, we propose a method to identify users based on web profile matching and further extend its effectiveness by incorporating the user's friend network. We collect and study real-life data from two popular social net- works and evaluate the importance of profile information. Machine learning algorithms are used in our experiments and we present results of pure profile-based user identification and demonstrate the benefits of incorporating the friend network in the classification process. We show that our combined method successfully identifies up to 93% of duplicated users across social networking websites.