AEA365 | A Tip-a-Day by and for Evaluators

Apr/13

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SNA TIG Week: Castle Sinicrope on Picking Your Social Network Analysis Software

Hello all, I’m Castle Sinicrope, Webmaster for the Social Network Analysis TIG since 2011 and Policy Analyst at Social Policy Research Associates, a research, evaluation, and technical assistance firm in Oakland, CA. For newcomers to social network analysis, picking the right software package can be a daunting task. Here’s an overview of four commonly used tools for visualizing and analyzing networks:

NodeXL: A free, open-source spreadsheet add-in for Microsoft® Excel 2007 and 2010, NodeXL integrates with social media tools like Twitter and Facebook, allows users to generate maps, and calculates common network statistics.

Strengths: Beginner friendly, active on-line support community

Cost: Free

Rad Resources: Marc Smith’s previous AEA365 post, co-authored how-to guide, Analyzing Social Media Networks with NodeXL: Insights from a Connected World, and YouTube introduction to NodeXL.

Gephi: Hailed as the “Photoshop for graphs,” Gephi is a free, open-source standalone program for interactively exploring and visualizing networks and complex systems. Gephi includes common statistics for social network analysis and supports main file formats from other software programs.

Strengths: Powerful and flexible visualization tool

Cost: Free

Rad Resources: Be enthralled by the dazzling Introducing Gephi video and learn with (and from) their online community support forum.

UCINET/NetDraw: Comprehensive and well-established, UCINET is an all-in-one program that supports advanced social network analyses and network visualization through an accessible user interface.

Strengths: Calculates sophisticated network statistics

Cost: $40 (students), $150 (faculty), $250 (corporate). Faculty and corporations can purchase site licenses at a discount. NetDraw, UCINET’s program for visualizing network data, can be downloaded for free here.

Rad Resource: Hanneman and Riddle’s Introduction to Social Network Methods, a comprehensive on-line textbook that introduces basics of social network analysis through UCINET.

R: Not for the faint of heart, R does not have a typical user interface. To succeed with R, you need to be comfortable with programming and writing your own code. The reward? Flexibility and ability to clean your data, visualize your networks, and generate network statistics, all in the same program.

Strengths: Very customizable and powerful

Cost: Free

Rad Resource: Stanford University’s R for Social Network Analysis website includes step-by-step instructions for getting started with SNA in R.

Stay tuned for demo posts for NodeXL, Gephi, and UCINET later this week!

The American Evaluation Association is celebrating Social Network Analysis Week with our colleagues in the Social Network Analysis Topical Interest Group. The contributions all this week to aea365 come from our SNA TIG members. Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365@eval.org. aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

1 comment

  • rick davies · May 1, 2013 at 3:22 am

    Can you add two more packages to the list being discussed?

    yED at http://www.yworks.com/en/products_yed_about.html
    This is great for drawing networks, for example when trying to articulate a theory of change in network form. The results can be exported in graphml format and read by many other SNA packages. This is free.

    Visualyzer at http://socioworks.com/ (and related SNA packages there). This is very user friendly and can use and export formats used by other packages. It is now reasonably priced

    I have used both packages over the years, along with others more well known such as UCINET. I have no commercial interest in either package

    Reply

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