***** To join INSNA, visit http://www.insna.org ***** Dear colleagues, my question deals with the "spdep package" in the R environment. I have a social network consisting of roughly 20,000 actors. The data describing this network is stored in an Access database in two separate tables: The first table includes the relationships between pairs of actors in the form: Actor1 - Actor 2 - Tie_strength. The second table includes information about each actor in the form: Actor_ID - Variable1 - Variable2 - ... My objective is to see whether actors that are related to each other tend to have similarities in one of the variables (e.g. Variable1). I would like to do this by calculating a "Moran's I" statistic, which in my understanding is essentially a measure of network autocorrelation. Browsing the Internet, I found the "spdep package" that seems to be well suited for this task. However, my issue is that the "spdep package" has initially not been developed for social network analysis but for spatial statistics. Hence, the problem I'm having is that I do not know in which format I should import my data into R so that I can use it within the "spdep package". I am familiar with using R and know how to generally import data by using the read.csv function. The problem is that the "spdep package" requires data in a very special format (a so-called neighbors list) and I do not know how I can get my data from above into this type of format. Does anyone have some experience with the "spdep package" and can point me into some direction? Or is there another easier to use tool that I could use to do my "Moran's I" calculation? Thanks very much for your help in advance. I will post a list of all responses received to this question on the list. Best, Michael Michael Haenlein Assistant Professor of Marketing ESCP-EAP European School of Management 79, Avenue de la République | 75011 Paris | France _____________________________________________________________________ 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.