On 09/29/2012 09:22 PM, cc wrote:
Great, glad I could have helped! Before I jump to the git version, I'm curious as to whether graph-tool can calculate eigenvector centrality for signed networks. Bonacich and Lloyd suggest a eigenvector measure on a symmetrical adjacency matrix to infer status (2004) <http://www.sciencedirect.com/science/article/pii/S0378873304000449> . That is to say, an edge signed with -1 represents a negative relationship, and an edge signed with 1 represents a positive relationship, and thus those with negative and positive eigenvector centralities belong in different "cliques". Is it possible to arrive at this idea through the eigenvector centrality implemented in graph-tool if one were to assign -1 or 1 as edge weights in the graph? I.e., does the implemented algorithm take into account negative vs. positive weights? Sorry to jump the gun here, but the extensibility of graph-tool to more obscure measures is intriguing...
This should work without a problem. The function in graph-tool implements the power method, which works for any matrix, and always converges as long as the largest eigenvalue is non-degenerate. Cheers, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>