It's very easy to become enamoured with the visualisations and potential of network analysis, and see it as an end unto itself. This is one reason why I think that network analysis is a diagnostic methodology. It can aid understanding, but there are obvious limitations. For example any visualisation is a representation, or report of, data collected at particular time in a particular place. We all know human systems are dynamic, so it's reasonable to assume data will degrade and the network will change.
It is also a common mistake to think the visualisation, or the data matrix, represent analysis: they do not! I think Drew Conway , who is a political scientist, makes the point very well when he says:
"Simply because your data links people and you can visualize that, it does not mean you have performed network analysis. This is akin to displaying a line plot of some stock's price over a quarter and claiming you have performed statistical analysis-no-you have reported data. As with all other statistical processes, network analysis is meant to draw meaning and inference from the structure, which requires an understanding of these methodologies, their strengths and limitations".
