A Unifying Framework for Measuring Weighted Rich Clubs

作者：Alstott Jeff^*; Panzarasa Pietro; Rubinov Mikail; Bullmore Edward T; Vertes Petra E

来源：Scientific Reports, 2014, 4(1): 7258.

DOI：10.1038/srep07258

Network analysis can help uncover meaningful regularities in the organization of complex systems. Among these, rich clubs are a functionally important property of a variety of social, technological and biological networks. Rich clubs emerge when nodes that are somehow prominent or %26apos;rich%26apos; (e.g., highly connected) interact preferentially with one another. The identification of rich clubs is non-trivial, especially in weighted networks, and to this end multiple distinct metrics have been proposed. Here we describe a unifying framework for detecting rich clubs which intuitively generalizes various metrics into a single integrated method. This generalization rests upon the explicit incorporation of randomized control networks into the measurement process. We apply this framework to real-life examples, and show that, depending on the selection of randomized controls, different kinds of rich-club structures can be detected, such as topological and weighted rich clubs.

• 出版日期2014-12-1