Experiences with Phonebook-Centric Social Networks

Social networks are becoming more and more popular nowadays. The increasing capabilities of mobile phones enable them to participate in such networks. The phonebooks in the mobile devices represent social relationships, that can be integrated in the social networks. Following we refer to this solution as phonebook-centric social networks. Such networks provide a synchronization mechanism between phonebooks of the users and the social network which allows detecting network members listed in the phonebooks (semi-) automatically. The detection of those members is based on the similarity of the personal data, e.g., similar name, same phone number, address, etc... Users can mark similarities between their phonebook contacts and members in the network. After this, if one of their contacts changes her or his personal detail, it will be propagated automatically into the phonebooks, after considering privacy settings. Synchronization time and energy consumption for synchronization on the mobiles and the scalability of the system strongly depend on the number of users and similarities. We have implemented a phonebook-centric social network, called Phonebookmark and investigated the structure of the network. We experienced that the distribution of similarities follows a power law, as well as the distribution of the in- and out-degrees in the social network. In this paper we propose a model for estimating the total number of similarities and we show that this estimation applies very well to the historical data of Phonebookmark.