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Dear colleagues,

For a research project I'm currently working on, I need to generate a large number of random graphs. Currently, I'm doing this using the "igraph" library within the R computing environment and specifically the functions "" and "". The problem is, however, that neither an Erdos-Renyi random graph nor a Watts-Strogatz small world graph have the same set of characteristics than real life social networks.

For this reason, I'd like to try out a different method, namely the one described in a paper by Matthew Jackson and Brian Rogers ("Meeting strangers and friends of friends: How random are social networks"), published in the American Economic Review (Vol. 97, No. 3) in June 2007. I have a Mathematica code that is able to generate random graphs consistent with this model, but my knowledge of Mathematica is rather limited. Additionally, I'm running my main analysis in R, which means that at the moment I'm generating graphs in Mathematica, export them to a txt file and import them again into R. Evidently, this process is quite manual and tedious.

My question is therefore whether anyone knows of a code within the R computing environment that is able to generate random graphs consistent with the Jackson & Rogers model. Alternatively, it there is some way to call Mathematica within R that would be helpful as well.

Thanks very much for letting me know,


Michael Haenlein
Professor of Marketing
ESCP Europe - The School of Management for Europe
79, Avenue de la République | 75011 Paris | France

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