Multi-objective optimization to identify key players in social networks

Identification of a set of key players in a given social network is of interest in many disciplines such as sociology, politics, finance, and economics. Each of the current algorithms for this task addresses a single objective, but does not perform well from the perspective of other objectives. In real life applications, we need a set of key players which can perform well with respect to multiple objectives of interest. In this paper, we propose a new perspective for key player identification, based on optimizing multiple objectives of interest, and illustrate its applicability. In addition we propose an algorithm to select the most suitable sets of key players when the user can identify a subset of objectives as important. We apply these algorithms to the Eventual Influence Limitation problem and show that our multi-objective approach outperforms previous approaches.