The m-Ranking of Nodes in Weighted Networks

Abstract

Identifying pivotal nodes within complex systems has emerged as a cornerstone of network science, offering both profound theoretical insights and significant practical utility. However, only a limited number of centrality measures are applicable to weighted networks. Addressing this limitation, the m-Ranking method has been introduced as a robust analytical framework that evaluates node hierarchy by integrating connection density with the specific intensity of link weights. This approach is notably versatile and maintains high precision in weighted network environments.