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Re: How to measure the distribution of an attribute among the nodes of a network?

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Wed, 13 Jan 2016 01:13:35 +0100

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 ```***** To join INSNA, visit http://www.insna.org ***** Thank you all for your insights! ------------ A new MOOC by EMLYON CODAPPS : Coding Mobile Apps for Entrepreneurs. https://www.coursera.org/learn/codapps Assistant Professor EMLYON Business School +33 (0)4 78 33 77 25 Mobile : +33(0)6 59 08 33 92 Skype and Twitter : @seinecle http://www.clementlevallois.net -----Message d'origine----- De : Vladimir Batagelj [mailto:[log in to unmask]] Envoyé : mardi 12 janvier 2016 14:18 À : LEVALLOIS Clément Objet : Re: How to measure the distribution of an attribute among the nodes of a network? On 12-01-2016 13:27, LEVALLOIS Clément wrote: > ***** To join INSNA, visit http://www.insna.org ***** > > Hi, > > Indeed my formulation was not clear. Refining my statement, I think a > possible solution can appear: > > - Being evenly distributed in the network would mean that the distance > (shortest paths) between the nodes bearing this attribute value is > comparably close to the distance between the same number of nodes > randomly picked from the entire set of nodes of the network. > > Does it make sense? 2 things: > - it does not depend on a notion of communities > - I might be wrong but the formulation above seems quite > computationally intensive > > Clement    If U is a small community then usually N(U) will have large    intersection with U and N(U) setminus U will be relatively    small - the value of W will be small.    We get large values of W when U is large or U contains hubs -    nodes with very large degree.    It is very fast. The time complexity is linear in number of links.    Vlado -- Vladimir Batagelj   IMFM - Institute of Mathematics, Physics and Mechanics   Jadranska 19, 1000 Ljubljana, Slovenia and   University of Primorska, Andrej Marušič Institute, Koper T: +386 1 4766 672 W: http://vladowiki.fmf.uni-lj.si/doku.php?id=vlado ---- Ce message electronique et tous les fichiers attaches qu'il contient sont confidentiels et destines exclusivement à l'usage de la personne à laquelle ils sont adresses. Si vous avez reçu ce message par erreur, merci de le retourner à son metteur. Les idees et opinions presentees dans ce message sont celles de son auteur, et ne representent pas necessairement celles de l'institution ou entite affiliee dont l'auteur est l'employe. La publication, l'usage, la distribution, l'impression ou la copie non autorisee de ce message et des attachements qu'il contient sont strictement interdits. This email and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom they are addressed. If you have received this email in error please return it to the sender. The ideas and views expressed in this email are solely those of its author, and do not necessarily represent the views of the institution or company of which the author is an employee. Unauthorized publication, use, distribution, printing or copying of this e-mail or any attached files is strictly forbidden. _____________________________________________________________________ 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.```