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***** To join INSNA, visit http://www.sfu.ca/~insna/ ***** On Nov 16, 2003, at 2:26 PM, Vaughan wrote: > I would like to find out whether the network I have is a small world or > scale free network (or neither), however it is not obvious to me which > analysis in any of these software packages would tell me this. > > I have a background in psychology, rather than graph theory or > sociology so > some of the literature is a little mysterious to me. I have papers > which > define small world / scale free networks in mathematical terms but no > pointers as to how (and if) this is implemented in relevant software > packages. I know of no software packages that implement what you're looking for. JUNG (of which I am one of the developers) can generate small-world networks, but it does not, as yet, include mechanisms to evaluate how closely a given network resembles a small-world network. (In a sense, the question "is this a small-world network?" is not well-posed, because "small-world network" is a description of a statistical property; it's exactly analogous to asking whether data is normally distributed.) I assume that the question you'd really like to be able to ask is "how similar is the distribution of properties (e.g., degree) of this network similar to that of a small-world network?", and/or "what is the small-world network which is most similar to this network?", and similarly for scale-free networks. I don't know of a clean way to evaluate this; the general strategy that I would use would be to calculate the properties (e.g., degree distribution) for my network, and then find (via something like binary search on the generative parameter(s)) the small-world graph whose distribution most closely resembles that of your network. Then you can decide whether the match is close enough for your purposes. Hope this helps. If you'd like some assistance in implementing the scheme mentioned above in the JUNG framework (which can read basic Pajek .net files), please feel free to contact me. Regards, Joshua O'Madadhain jmadden@ics.uci.edu...Obscurium Per Obscurius...www.ics.uci.edu/~jmadden Joshua O'Madadhain: Information Scientist, Musician, Philosopher-At-Tall It's that moment of dawning comprehension that I live for--Bill Watterson My opinions are too rational and insightful to be those of any organization. _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.sfu.ca/~insna/). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.