SocialAction:

Integrating Statistics and Visualization

for Social Network Analysis

SocialAction is a social network analysis tool that integrates visualization and statistics to improve the analytical process.

LATEST NEWS

A journal article about SocialAction was recently published in IEEE Computer Graphics and Applications. See the full details in the papers below.

SocialAction won a VAST Mini-Challenge award for uncovering hidden structure in social networks over time.

There are also two recent conference publications about SocialAction!� In January 2008, techniques on how to guide a user through a complex data analysis task will be presented in the Canary Islands at IUI 2008.� In April 2008, case studies of how SocialAction led to insights among social network analysts will be presented in Florence at CHI 2008.� See the full details in the papers below.

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Overview

SocialAction aims to help researchers understand their social network data.� Please contact Adam Perer if you'd like to find out if SocialAction can help you! Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks.� However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner.�

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, SocialAction, could dramatically speed insight development.

Users can

  1. Flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers
  2. Aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest
  3. Untangle networks by viewing different link types separately, or find patterns across different edge types using overview visualizations.

For each operation, a stable node layout is maintained in the network visualization so users can make comparisons.

Participants

SocialAction in Action

SocialAction: Analyzing the Social Network of US Senators on Vimeo.

The following images demonstrate how SocialAction helps users make discoveries.

Click each image to view a larger version.

Understanding the Global Jihad Terrorist Network

Users begin with an overview of the entire social network.� On the left side, overview statistics that describe the overall structure are presented.� On the right, the network is visualized using a force directed algorithm. The gatekeepers are found using a statistical algorithm. Users filter out the unimportant nodes using a dynamic slider which simplifies the visualization while maintaining the node positions and structure of the network. Labels are always given priority so users can understand what the data represents. When user selects a node, neighbors are highlighted and details appear on the left.� In order to protect sensitive information, node labels have been anonymized except for those individuals publicly identified in the Zacarias Moussaoui trial.

Understanding Voting Patterns Among United States Senators

The social network of the U.S. Senators voting patterns in 2007, after Democrats took control. Republicans are colored red, Democrats blue and Independents maroon. Here, the partisanship of the parties appeared automatically (180 vote threshold). The social network of the U.S. Senators voting patterns. Here, the threshold is raised to 290 votes. The Democrats' relationships are much more intact than the Republicans. Details-on-demand are provided for Senator Whitehouse, the senator with the highest degree at this threshold.

Academic Publications

new!� Adam Perer and Ben Shneiderman: Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines, IEEE Computer Graphics & Applications 29, 3 (May/June 2009), 39-51.

Adam Perer and Ben Shneiderman: Integrating Statistics and Visualization: Case Studies of Gaining Clarity during Exploratory Data Analysis. SIGCHI Conference on Human Factors in Computing Systems (CHI 2008)

Adam Perer, Ben Shneiderman: Systematic Yet Flexible Discovery: Guiding Domain Experts through Exploratory Data Analysis. International Conference on Intelligent User Interfaces (IUI 2008)

Adam Perer, Ben Shneiderman: Balancing Systematic and Flexible Exploration of Social Networks. IEEE Transactions on Visualization and Computer Graphics (InfoVis 2006). 12(5): 693-700 (2006)

Adam Perer, Ben Shneiderman. Improving Interactive Exploration of Social Networks. International Sunbelt Social Network Conference (SUNBELT). (2006).

Adam Perer: Making sense of social networks. Extended Abstracts of ACM conference on Human factors in computing systems (CHI 2006) 2006: 1779-1782

Adam Perer, Ben Shneiderman. Orderly Analysis of Social Visualizations. Social Visualization Workshop at CHI 2006. (2006).

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OTHER Publications

December 21, 2007.� SocialAction is featured in Slate Magazine, which describes an analysis of the social networks of steroid users in Major League Baseball.�

Sponsorship

Early work on SocialAction and the case study evaluation method was supported by National Science Foundation grant SGER - 0633843: Developing Ethnographic Evaluations for Creativity Support Tools.

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Web Accessibility