Mining personal social features in the community of email users

Abstract

The development of structure analysis that constitutes the core part of social network analysis is continuously supported by the rapid expansion of different kinds of social networks available in the Internet. The network analyzed in this paper is built based on the email communication between people. Exploiting the data about this communication some personal social features can be discovered, including personal position that means individual importance within the community. The evaluation of position of an individual is crucial for user ranking and extraction of key network members. The new method of personal importance analysis is presented in the paper. It takes into account the strength of relationships between network members, its dynamic as well as personal position of the nearest neighbours. The requirements for the commitment function that reflects the strength of the relationship are also specified. In order to validate the proposed method, the dataset containing Enron emails is utilized; first to build the virtual social network and afterwards to assess the position of the network members. © Springer-Verlag Berlin Heidelberg 2008.