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Hi All -

I wanted to feedback the information I gathered regarding the software
comparisons / recommendations question posted to the UCINET and the SOCNET
groups.  (Sorry for the overlap if you are in both groups.)  My specific
question was about the software available for visualization and analysis of
longitudinal network data.

Below is a compilation of the different responses I received.

Thank you all for your help!

Joan Allatta

Doctoral Candidate

The Wharton School

[log in to unmask] <mailto:[log in to unmask]>


Mark Huisman and Marijtje van Duijn wrote a paper on software for social
network analysis; this paper provides a comparison of a number of different
software pkgs. It will appear next Fall as a chapter in the new SNA book of
Carrington, Scott and Wasserman:

Huisman, M. & Van Duijn, M.A.J. (2004). Software for social network
analysis. In P.J. Carrington, J. Scott, & S. Wasserman (Eds.) Models and
methods in social network analysis. New York: Cambridge University Press.

Write directly to Mark to obtain an advanced copy.  ([log in to unmask]
<mailto:[log in to unmask]> )


Zoomgraph at HP

You can try project:

Take a look at the movie links.  It demonstrates interactions in a company
(on a weekly basis) between individuals.  The system accepts data with any
kind of attributes, the ability to declare "states," and a way to move
smoothly between states.

Contact Eytan Adar at HP [[log in to unmask]] if you need any more info,


The combination of SoNIA and Siena could be a powerful means of analyzing
your longitudinal network data.

SoNIA was created so users could construct animations of dynamic networks
(whether you have continuous or discrete notions of time), browse
attribute-rich network data, and have a platform for testing and comparing
different layout techniques. Hence, SoNIA allows you to use a variety of
graphing algorithms, see the underlying process by which layouts are made
(i.e., cooling functions, fitness of distances to graph-coordinate space,
etc - so at least some comparison and discussion of "better" or "worse"
graphs can be had), and it minimizes artificial movement that arises from
animating across successive graphs. The end result is a dynamic network
visualization with meaningful movement. The documentation for SoNIA can be
found here
<> , here
<> , and in a
forthcoming American Journal of Sociology article that explains the theory
behind it
<> . Multiple empirical
studies using SoNIA are well under way and already under review.

Siena is a nice compliment because it enables you to analyze the
interrelation of networks and attitudes over time (or more broadly,
relational and nodal mechanisms). Documentation for Siena can be found with
the StocNet software here
<> , the Sunbelt satellite symposium, and in recent
Sociological Methodology (2003) pieces by Tom Snidjers and others (see
further down on the aforementioned webpage).


 Contact Daniel A McFarland [[log in to unmask]] for more info.


you might have a look at the 'sna' package for the R statistical computing
environment - available from <>

R has a non-trivial learning curve, but the folks on the R listserv are very
friendly and helpful.


Contact elijah wright [[log in to unmask]] for more info.


If you want to get a dynamic analysis/visualization over time, you

can also try our software <>  (similar to Sonja, but more


from Ning Yu at Indiana University

Here is a visualization I just generated for a Weblog research using Pajek.

There are original 5516 nodes(unique Weblog URLs that manually collected,
starting from 4 random chosen Weblogs) and I use cut-off at 10 in-degrees to
make the visualization readable. Actually I had the 5 in-degrees cut-off and
the main pattern is almost the same to cut-off at 10.

The reason we choose in-degree is that this research group concerns more
about the in-bound link to answer their research questions.

-- Here is a snapshot with full legend information:

-- Now comes a more dynamic one. If you have SVG viewer installed in you
computer (if not, you can download from Adobe website), open the following
page and you can see some check boxed in your right hand. Checking or
un-checking them will show or hide particular classes.

-- If you cannot read the file, here is a series of snapshots.

The classification is based on in-degree again. For example, in
classes_4.gif as , only node have over 59.71(well, 60 in this

case) wiill be shown

You can easily make animation using those snapshots.:)

For comparing different visualization software, I never did a literature
review on it.:P But I did tried a lot and find that actually those famous
software have similar function and all can be very powerful if you really
KNOW it. So it becomes a problem of whether it has good documentation and
whether you feel comfortable with the language it used if it is command line
based (e.g.GraphVis). Basically, the more users it owns, the more powerful
it is. Take Graphvis for example again, There are Perl class and Java
library provided by the users. You can find some social network analysis and
visualization tools under "research and resources" and "tools" on this page:

Ning Yu at Indiana University

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