You could start having a look at cran packages like sna or statnet, or search cran for "network" and you nfind a lot of packages!
On Wed, Dec 22, 2010 at 12:00 AM, EU JIN LOK <ejl...@hotmail.com> wrote: > > Dear R users > > I'm a novice user of R and have absolutely no prior knowledge of social > network analysis, so apologies if my question is trivial. I've spent alot of > time trying to solve this on my own but I really can't so hope someone here > can help me out. Cheers! > > The dataset: > I'm trying to predict the existance of links (True or False) in a test set > using a training set. Both data sets are in an "edgelist" format, where User > IDs represents nodes in both columns with the 1st column directing to the 2nd > column (see figure 1 below). Using the AUC to evaluate the performance, I am > looking for the best algorithm to predict the existance of links in the test > data (50% are true and rest are false). > > Figure 1: >> training > Vertices: 1133143 > Edges: 999 > Directed: TRUE > Edges: > > [0] 105 -> 850956 > [1] 105 -> 1073420 > [2] 105 -> 1102667 > [3] 165 -> 888346 > [4] 165 -> 579649 > [5] 165 -> 136665 > etc.. > > I'm having problems obtaining the probability scores for the links / edges as > most of the scores are for the nodes. An example of this is the graph.knn and > page.rank module in igraph. > > So my questions are: > 1) What do I need to do to obtain the scores for the links instead of the > nodes (I presume it must be a data preparation step that I must be missing > out)? > 2) Which R package would be the best for running the various techniques - > Jackard index, Adamic-Adar, common neightbours, PropFlow, etc > 3) How to implement a supervised learning method such as random forest (I am > guessing I need to obtain a feature list but again, how can I get the scores > for the edges)? > > Hope I've explain my questions well but do let me know if more clarification > is need. > > Thanks in advance > Eu Jin > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
