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[igraph] Negative eigenvector centrality?
From: |
Nathan Cobb |
Subject: |
[igraph] Negative eigenvector centrality? |
Date: |
Thu, 22 Oct 2009 11:38:54 -0400 |
User-agent: |
Microsoft-Entourage/12.20.0.090605 |
I'm working with a series of large, sparse communication networks
(v~7-15,00;e~10-30,000) The networks are initially directed but not
weighted.
Using iGraph 0.52 with the Python interface I'm getting back negative
Eigenvector centrality scores no matter what I do. The code looks something
like:
target_graph.add_vertices(len(vertices))
target_graph = target_graph.add_edges(edges)
target_graph.to_undirected()
target_graph.simplify(multiple=False,loops=True)
eigenvector_centrality = target_graph.eigenvector_centrality(scale=False)
The resulting values seem to range somewhere between -1 and 0 (never
positive.)
Am I missing something conceptually here, or am I hitting a bug?
Thanks,
- Nate
Nathan Cobb, MD | Research Investigator
T 202-454-5745 F 202-454-5785
Schroeder Institute for Tobacco Research and Policy Studies
American Legacy Foundation
1724 Massachusetts Avenue, NW, Washington, DC 20036
- [igraph] Negative eigenvector centrality?,
Nathan Cobb <=