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Re: [igraph] finding suitable network centrality measure

From: Hernani Oliveira
Subject: Re: [igraph] finding suitable network centrality measure
Date: Thu, 8 Dec 2016 08:34:06 +0000

HI Sahab,

Eigenvector centrality is used to measure the number of connections of the neiborhing nodes of the nodes you are getting the measure. In a directed graph, I think you can try to use a measure of eigenvector centrality that takes into account the in degree and out degree of the nodes to take into account for the direction of the interactions.
Maybe you could use closeness centrality that will show the node where that is closer to most of other nodes in terms of the interactions they share. Check out.


2016-12-07 23:24 GMT+00:00 shahab <address@hidden>:

I am looking at a problem where I need to measure eigen vector centrality in a an undirected graph where edges are weighed by the amount interaction between two nodes (we call this  weight as WI) and each node itself is also have a weight showing its importance ( we call this weight WP).

The goal is to find the most influential node in the network.

I sought that the best way is to transform this graph to directed graph, where  each edge from A->B is weighted by:  WP (of node A) * WI (edge A-B)/(sum of all WIs associated. to node A)

I just wonder if this is a reasonable solution to be done using igraph:: eigen_centrality?


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