Link communities R package

A while ago, I wrote about Rob Spencer over at Scaled Innovation‘s implementation of the algorithm for detecting link communities. Today, I am happy to report on another exciting development for the alorithm. Alex Kalinka from the Tomancak lab at the Max Plank Institute (MPI-CBG) has written a great implementation in R, called linkcomm. It is now up on CRAN:

http://cran.r-project.org/web/packages/linkcomm/index.html

While everything is excellent, the graphics are particularly beautiful – much prettier than our own visualizations – check out the colored link dendrogram plot (from the CRAN website)

And the spatial network layout options are great as well; the various community visualizations are simple, elegant, and very pretty:

The panel on the left shows a 'Spencer circle' layout, while the panel on the right shows a Fruchterman-Reingold layout. From the linkcomm documentation.

In addition, there are many neat features. For example, linkcomm allows you to visualize sub-communities by themselves. Alex has also published an Application Note in Bioinformatics about the implementation, so take a look if you’re interested:

http://bioinformatics.oxfordjournals.org/content/early/2011/05/19/bioinformatics.btr311.abstract (open access).

We also link to the package from our link communities download page.

Tu Vuò Fà L’Americano

I’m excited to leave Boston for a bit to participate in ARS’11: The Third International Workshop on Social Network Analysis, Collaboration Networks and Knowledge diffusion: Theory, Data and Methods. It takes place in Naples, Italy this week, and the speaker line-up looks exciting (despite the fact that they invited me) [1].

Here’s a bit of text from the official description:

ARS’11 International Workshop is a follow up to two very successful previous editions ( ARS’07 and ARS’09) and will be held on June 23-25, 2011 in Naples (Italy).
Collaboration networks attract a lot of attention in many fields and are considered a key element in the advancement and dissemination of knowledge in scientific as well as in socio-economic domains. The workshop has the objective of presenting the most relevant results and recent developments in the areas of Collaboration Networks, Innovation Networks and Knowledge Diffusion.

The workshop also aims to deepen existing scientific cooperation between Social network analysts, to establish new cooperation between researchers, and to provide a forum for exchange of ideas among them.

The workshop topics include:

  • Collaboration theory
  • Analysis of innovation networks in economics environments
  • Sources of collaboration data
  • Social Network Analysis methods for collaboration data

Notes:

[1] I stole the idea for this elegant, faux self deprecating plug from Aaron Clauset’s blog.