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The short answer is: there is no single R package that will do all the
things that you mention.
The somewhat more extensive answer is:
There are two main R packages that provide facilities to store,
manipulate and visualize network data. These are "network" and
'igraph". Technically speaking each package provides a specialized
class of R data objects for storing network data plus additional
functions to manipulate and visualize them. Each package has its
relative strengths and weaknesses, but by and large you can do most
basic network data operations and visualizations in both packages
equally easily. Moreover, you can convert network data objects from
"network" to "igraph" or vice versa with functions from the
Calculating basic network statistics (degree, centrality, etc.) is
possible for both types of objects. For "igraph" objects, functions
for these purposes are contained in "igraph" itself. For "network"
objects, most of the classical SNA routines are contained in the "sna"
Community detection algorithms (e.g. Newman-Girvan) are available only
in the "igraph" package.
"Fancier things", especially statistical models for networks (ERGMs
etc.) are available in various packages that were build around the
"network" package and jointly constitute the 'statnet' suite
(http://www.statnet.org/). There is also "tnet" package with some more
routines for among other things two-mode networks, which borrows from
both "network" and "igraph" world. And of course there is RSiena for
estimating actor-oriented models of network dynamics which is not
related either "network" or "igraph".
As for matrix algebra, it is obviously available within R itself.
My recommendation would be to have a look at both "igraph" and
"network" and pick the one which seems easier to you as far as
manipulating and visualizing networks is concerned. Have a look at the
documentation of these packages (e.g. on
http://www.rdocumentation.org/) and at tutorials on e.g.:
- statnet website (http://www.statnet.org/)
- igraph homepage (http://igraph.sourceforge.net/)
- R labs by McFarland et al (http://sna.stanford.edu/rlabs.php)
- Slides and scripts to my Sunbelt workshop
It does not really matter whether you pick "igraph" or "network" as
you can aways convert your network to the other class with 'asIgraph'
or 'asNetwork' functions from "intergraph" package and take advantage
of the functions available in the "other world".
I hope this helps
On Wed, Oct 9, 2013 at 1:19 AM, Jesse Sayles <[log in to unmask]> wrote:
> ***** To join INSNA, visit http://www.insna.org *****
> Hi SOCNET,
> I am curious if anyone can recommend one R package over another. I have been
> reading about the various packages and am a little confused about which
> would be best to use.
> I have a basic understanding of R, but have not done any network analysis
> with it. I have been using UCINET, which is great, but I want to start doing
> some things in R for efficiency sake and just to know how to do these
> analyses in R.
> I am not doing anything too fancy. I am calculating basic network measures
> (e.g. degree, betweeness) and want to be able to calculate subgroups (e.g.
> Girvan-Newman, Factions, K-cores, etc.). But maybe one day I will do fancier
> things. And of course I will want to visualize the networks in R.
> I also have to do a lot of mathematical transformations of my data and the
> UCINET matrix algebra interface is great for this (e.g. adding or
> multiplying corresponding cells across matrices).
> So, I would want to make sure that what ever R package I use can do all of
> these things, which they all seem to be able to do. This brings me back to
> my original question as to if someone can recommend one package over the
> Any advice on which R package to start learning would be welcome.
> Thank you
> Jesse Sayles
> PhD candidate
> School of Geographical Sciences & Urban Planning
> Arizona State University
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