Nov 21, 2009 at 4:02 PM
Edited Nov 21, 2009 at 4:20 PM
Hello! Thank you for your interest in NodeXL.
You are touching on issues of social network analysis theory and method that depend on details of the data and the research question. You may want to review the International Network for Social Network Analysis site at http://www.insna.org - in particular,
consider joining the SOCNET-L email list where a great group of people with deep SNA experience gather to discuss these kinds of questions.
My short answer is: no; I would not simply add those values together. The "key metrics (ie. Degree, Betweenness and Closeness centrality and Eigenvector centrality)" all mean very different things.
You may want to explore the ways these values change over time in the network. Each metric has a description that could help you interpret what changes in those values mean in your dataset (see:
For example, increasing density for the whole graph (a metric that is reported on the Overall Metrics worksheet) suggests that more relationships are being created over the intervening time, while older relationships are being maintained. If a particular
node's eigenvector centrality increases significantly, they may have created new important relationships or their friends may have developed new connections.
NodeXL can implement almost any model you decide to create by building formulas that relate the node metrics and other attributes. These compound metrics can be mapped to any display attribute using the Auto-fill columns feature.