***** To join INSNA, visit http://www.sfu.ca/~insna/ ***** Hi all, since it looks like email networks is becoming a hot topic in the list we would like to point you to a couple of PDF documents where we analyze in detail the email network of a mid-sized university (composed of 1700 nodes including academic, administration staff and PhD students). The main conclusions derived from these works are: - The e-mail network is indeed a social network as pointed out by Prof. Krackhardt that reveals the informal network behind the formal chart of any organization. - The community structure can be identified by the algorithm proposed by Girvan and Newman (PNAS 99, 7821-7826, 2002). It determines perfect communities (except ambiguous nodes) and provides a binary tree where the leaders appear at the ending leaves. - The community structure presents a stricking self-similar structure, that it is not an artifact of the community identification algorithm as we show in the article. It suggest that a self-organized universal mechanism is driving the informal network formation. The first document, more "physicist oriented", was posted in the Los Alamos archive on 22 Nov 2002, and is currently being considered to be published in a physics journal. The second document, which has been written for a wider audience, exploits the details that can be of interest from an organizational point of view: identification of communities (schools, departments, research groups, ...) in the university, leadership role, relation between the centers, distances in the social network, and so on. Both documents can be downloaded from our group of Physics of Complex Systems web pages http://galadriel.ffn.ub.es/socnet.html This work was presented by A. Arenas in the 7th Granada Seminar on Computational and Statistical Physics (held in Granada, Spain, 2-7 September 2002) http://ergodic.ugr.es/cp/pages/7th2002.htm The recently paper written by Huberman et al. presents a nice algorithm that corroborate our results in a company half of the size of our university. Nevertheless, the algorithm of Girvan and Newman discriminates communities up to the size of individual persons and is a matter of choice to define the minimal size we assign to a community. We argue that the GN algorithm complemented with the full visualization of the binary tree is an excellent tool for management purposes. _____________________________________________________________________ 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.