Although both statistical methods and visualizations have
been used by network analysts, exploratory data analysis
remains a challenge.  We propose that a smooth integration
of these technologies in an interactive exploratory tool
could dramatically speed insight development. To test the
power of this integrated approach, we created a novel social
network analysis tool, SocialAction, and conducted four
long-term case studies with domain experts, each working
on unique data sets with unique problems.  The case studies
show that the integrated approach in SocialAction led to
significant discoveries by a political analyst, a
bibliometrician, a healthcare consultant, and a counter-
terrorism researcher.  Our contributions demonstrate that
the integration of statistics and visualizations improves
exploratory data analysis, and that our methodology for
long-term case studies captures the research processes of
data analysts.

Further information is available at:  http://www.cs.umd.edu/hcil/socialaction/

Bio: Adam Perer is a doctoral candidate of Computer Science at the
University of Maryland, College Park.  His advisor is Dr. Ben
Shneiderman and he is a member of the Human-Computer Interaction Lab.
His research interests include human-computer interaction, information
visualization, patterns of personal communication, and social
networks.  His dissertation work is focused on improving exploratory
data analysis by smoothly integrating statistical algorithms and
information visualizations.  His SocialAction project has helped
political analysts, bibliometricians, counter-terrorism experts and
healthcare consultants understand complex social networks.  He has
also been a visiting researcher at the Institute for Defense Analyses,
Xerox PARC, and Microsoft Research.