Shapley-Based Analysis of the Leadership Formation in Social Networks
The dynamic nature of networks formation requires the development of multidisciplinary methods for the effective social network analysis. The research presented in this chapter is motivated by the necessity to overcome the limitation of using analytical methods from the originally disconnected research domains. Hence, the authors present an approach based on techniques from different areas, such as graph theory, theory of algorithms, and game theory. Specifically, this chapter is based on the analysis of how an agent can move towards leadership in real-life socioeconomic networks. For the agent's importance measure, the authors employed a Shapley value concept from the area of cooperative games. Shapley value is interpreted as the node centrality that corresponds to the significance of the agent within a socioeconomic network. Employing game theoretic concept, the authors introduced an algorithmic approach that detects the potential connectivity modifications required to increase an agent's leadership position.