Finding clusters of CRAN packages using igraph by Andrie de Vries.
From the post:
In a previous post I demonstrated how to use the
igraphpackage to create a network diagram of CRAN packages and compute the page rank.Now I extend this analysis and try to find clusters of packages that are close to one another.
…
Andrie assigns labels to the resulting groups and then worries:
With clusters this large, it’s quite brazen (and possibly just wrong) to try and interpret the clusters for meaning.
Not at all!
Without grouping and labeling, there is no opportunity to discover how others might group and label the same items. We may all stare at the same items but if no one groups or labels them, we can walk away with private and very different understandings of how items should be grouped.
I remember a scifi novel where one character observes “sheep are different from each other,” to which another character added, “but only to other sheep.” Our use of different groupings isn’t all that is important. The reasons we see/give for creating different groupings are important as well.