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The LINKS Center at the University of Kentucky is offering its annual 1-week summer workshop on social network analysis June 2-6, 2014 on the University of Kentucky campus.  The workshop features sessions by Filip Agneessens, Steve Borgatti, Dan Brass, Rich DeJordy, Martin Everett, Dan Halgin, Jeff Johnson, David Krackhardt, Joe Labianca, Ajay Mehra, Tom Valente and more. Students pay half-price, and there is a 20% discount for registering before April 15. To sign up, visit Registration opens today!


The workshop features four major, concurrent tracks for the first four days, followed by three choices of area-specific sessions on the final day. At the end of each day, we also offer multiple short modules on specialized topics. Finally, we offer a number of 45-minute consultations with LINKS Center staff to discuss your own research.

MAJOR TRACKS (4 days each; Monday-Thursday)

Introduction to Social Network Analysis. Led by Dan Brass and Dan Halgin (U. of Kentucky), with special guest David Krackhardt (Carnegie-Mellon). Includes a theoretical and empirical overview of the field, followed by a comprehensive survey of the concepts and methods of social network analysis, including data collection, data management, centrality, social capital, cohesion, and hypothesis testing. In addition, participants learn how to use network analysis software, including UCINET and NetDraw.

Analyzing Social Network Data. Led by Rich DeJordy (Northeastern). A more software- and data-oriented version of Introduction to SNA that covers most of the same topics as Intro but focuses more on using the software and devotes a bit more time to interpreting the equations & formulas that define many network concepts.  Includes lab sessions in which participants work through analysis exercises using the UCINET and NetDraw software.

Advanced Network Analysis. Led by Steve Borgatti (U. of Kentucky). For people interested in both a deeper and broader look at network concepts and methods. Topics include advanced centrality methods, measuring network change, advanced approaches to 2-mode data, analyzing negative ties, working with multiple relations, and integrating node attributes with network measures. The advanced session also introduces participants to UCINET’s command-line facility and batch processing of files.

Stochastic Network Models. Led by Filip Agneessens (University of Surrey).  This course provides an introduction to exponential random graph models (ERGMs) and stochastic actor-based models for network dynamics (as implemented in SIENA). The course will focus on hands-on use of MPNet and RSiena and on the interpretation of output. An introduction to the R analysis language (needed for RSiena) will also be provided during the workshop.

AREA TRACKS (1 day each; Friday)

Networks and Health. Led by Tom Valente (USC). Social network theory and method in the context of understanding health-related behaviors, interventions and disease epidemiology.

Networks and Leadership. Led by Ajay Mehra (Kentucky). Applying the social network perspective to leadership in organizations.

Networks and Intelligence. Led by Curtis Hampton (Leidos/SAIC) and Phil Willburn (Center for Creative Leadership; formerly Director of Social Network Analysis Training at SAIC). An introduction to how to use social network analysis to answer key intelligence and law enforcement questions using bulk data.

Recent Advances in SNA. Led by Martin Everett (U. of Manchester). A discussion of new methods and concepts in network analysis, including new approaches to handling negative ties.

MINI-MODULES (1.5 hours each, Monday-Thursday after 4pm)

The mini-modules are short sessions on specialized topics. Some focus on research design topics, others on using specialized software, and still others on handling particular kinds of data. Anticipated offerings include the following:

Managing your IRB. Tips on approaching your IRB with a network research design.

Obtaining and managing your network research site. Organizations are sometimes wary of network studies. We share our experience in managing these fears. We also share techniques for maximizing the quantity and quality of survey responses.

Choosing a research design. How to choose between whole network approaches and personal (egonet) designs.

Introduction to R. Quick introduction to using the R analysis language, particularly in the context of analyzing network data.

Introduction to E-Net. A tutorial on using the E-Net program for analyzing ego network data collected using a personal network research design (i.e., where respondents report on ties with alters who are not themselves respondents in the study).

Cognitive Social Structure (CSS) data. How to collect, analyze and theorize about CSS data, in which respondents are asked for their views of the entire network, not just their own ties.

2-mode data. Working with 2-mode data, including data obtained by cutting and pasting online tables of transactions or memberships.

Negative ties. How to collect, analyze and theorize about negative ties.

Network visualization. Approaches to visualizing relational data.

Data lab. (Offered daily) Bring your data and work with us to solve data management and analysis issues.

1-ON-1 CONSULTATIONS (45-minute slots available Tuesday-Thursday)

Discuss your research in depth with Joe Labianca, Jeff Johnson, Ajay Mehra, or Scott Soltis.


For more information, please visit the workshop website:

Please note that sessions are capped at about 55 participants, so you might want to register early.



Steve Borgatti



Stephen P. Borgatti

Paul Chellgren Endowed Chair of Management

LINKS Center for Social Network Analysis

Gatton College of Business and Economics

University of Kentucky

Lexington, KY 40508-0034 USA

E-mail: [log in to unmask]; [log in to unmask]

Tel: +1 859 257-2257 (O); +1 512 843-2674 (Google Voice); Fax: #1 859 904-2039    

Skype: steve.borgatti






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