***** To join INSNA, visit http://www.insna.org ***** Hello everybody, You might be interested in the following brief report "Cumulative Rank Aggregation of a Family of Network Centrality Indices" that I've just entered in my Medium blog: https://urldefense.proofpoint.com/v2/url?u=https-3A__medium.com_-40mosabou_cumulative-2Drank-2Daggregation-2Dof-2Da-2Dfamily-2Dof-2Dnetwork-2Dcentrality-2Dindices-2De625a76bf7e4&d=DwIBaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=KKhLpuoSdgNSblj5QR8GGUVheVaGB91lw9aMaPeyHVY&s=qiuVA8Rto15u_Dhmq4ASKtLkZOz4f-KZba61k28Bv54&e= A growing number of centrality indices are used today in social network analysis. The purpose of using all these network centrality measures is that through them one might be able to identify the most important nodes according to a variety of structural criteria (like nodal degree, closeness, betweenness, eigenvector, PageRank etc.). Moreover, computations (in Python, R etc. or standalone applications) may very easily derive the tables of various centrality indices of network nodes. Therefore, knowing a good deal of network nodal centralities, the crucial question would be how to make sense for all such indices in a illuminating way that would account for the structural features that an empirical network exhibits. What I am proposing here is a methodology for a cumulative ranking of network nodes according to the scores that each node possesses, not on a single centrality measure, but on a whole group (a family) of centrality measures. Any remarks, corrections, comments, suggestions etc are more than welcomed. Best, --Moses _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.