This paper presents an application of information theory to identify sets of key players in social networks. First, we define two entropy measures that we use to analyze the structural properties of a social network. Then, we propose a new method aimed at finding a set of key players that solves the KPP-Neg and KPP-Pos problems. Our preliminary experimental results indicate that the entropy measures can be used effectively to identify a set of key players in a social network.
Abstract. The paper presents FMOPSO a multiobjective optimization method that uses a Particle Swarm Optimization algorithm enhanced with a Fuzzy Logic-based controller. Our implementation makes use of a number of fuzzy rules as well as dynamic membership functions to evaluate search spaces at each iteration. The method works based on Pareto dominance and was tested using standard benchmark data sets. Our results show that the proposed method is competitive with other approaches reported in the literature.
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