***** To join INSNA, visit http://www.insna.org ***** You may find it useful to look into entropy statistics. I did a paper in 1991 entitled The Static and Dynamic Analysis of Network Data Using Information Theory, Social Networks 13 (1991) 301-45. You can find it at my website at http://www.leydesdorff.net/list.htm . With best wishes, Loet ________________________________ Loet Leydesdorff Amsterdam School of Communications Research (ASCoR), Kloveniersburgwal 48, 1012 CX Amsterdam. Tel.: +31-20- 525 6598; fax: +31-20- 525 3681; [log in to unmask] ; http://www.leydesdorff.net/ > -----Original Message----- > From: Social Networks Discussion Forum > [mailto:[log in to unmask]] On Behalf Of Nick Guenther > Sent: Wednesday, March 29, 2006 3:16 AM > To: [log in to unmask] > Subject: Re: Advice needed regarding longitudinal network data > > ***** To join INSNA, visit http://www.insna.org ***** > > On 3/28/06, Srikanth <[log in to unmask]> wrote: > > ***** To join INSNA, visit http://www.insna.org ***** > > > > Hello, > > I am trying to solve the following problem: I have > relationship data > > collected at various points in time regarding the participation of > > different members in a discussion group. Data were accumulated > > periodically, so the network at time T+1 consists of the mapping of > > all discussions that have occurred in the period between T and T+1. > > The data are in the form of adjacency matrices. I need to > compare the > > networks that existed at different time periods. > > I was just reading an article in Science by Gueorgi Kossinets > and his advisor Duncan Watts that did a longitudinal study of > a university (that I only discovered I had a copy of because > of reading the archives here!). Here's the link: > http://www.sciencemag.org/cgi/content/short/311/5757/88 > > They had continuous data but most of their techniques should > still apply to you. In fact, it occurs to me that you are > probably wrong to just compare the network at T, T+1... > because the network is probably not discrete like that, but > instead each past state has a varying amount of influence on > the present. > > You'll want to read the 'supporting online material' if you > have access to it; it has the 'methods' section. Some excerpts: > > They define a "sampling period" tau to determine which links > are considered ongoing links, and which are considered > broken. In their study they chose Tau=60 days which they > figured out by analyzing the distribution of communications > (95% of responses came within 60 days). > > What is your goal in your study? I'm still just learning SNA > but I keep hitting up against that the appropriate technique > really really really depends on the data. > > -Nick Guenther > > _____________________________________________________________________ > SOCNET is a service of INSNA, the professional association > for social network researchers (http://www.insna.org). To > unsubscribe, send an email message to [log in to unmask] > containing the line UNSUBSCRIBE SOCNET in the body of the message. > _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.