Introduction to Social Network Analysis

A 2-Day Seminar Taught by Stephen Borgatti, Ph.D. 

Read reviews of this course


Interest in social networks has been climbing exponentially since the 1970s. For social scientists, networks can be seen as a fundamental adaptation that facilitates both the coordination and distribution of resources, while simultaneously maintaining the flexibility of independent agents. For physical scientists, networks can be seen as universal structures underlying everything from molecules to galaxies. And for mathematicians and computer scientists, networks provide an abstract and propitious way of representing problems.

The field of social network analysis consists of a vocabulary of theoretical and mathematical concepts for investigating network phenomena, along with a distinctive data model and set of methodologies for collecting and analyzing network data. This course provides an introduction to doing research on social networks. The course is very hands-on, emphasizing mastering the software and using the concepts and methods to answer research questions. It also covers use of network analysis in applied settings such as management consulting and criminology.

The course is heavily hands-on, so you must bring a laptop with UCINET installed. Power outlets will be provided at each seat. 


WHO SHOULD ATTEND

This course assumes no prior knowledge of network analysis, but does assume some background in social science research methods, including survey design and simple regression analysis. It is also helpful but not necessary to be familiar with the basics of matrix algebra, particularly matrix multiplication.


Computing

We will use the UCINET software package, which can be downloaded from http://tinyurl.com/ucinet. The software is not free, but can be used on a trial basis for 60 days. The course is heavily hands-on, so you must bring a laptop with UCINET installed. Note that UCINET is a Windows program and will not run on a Mac except through Boot Camp or a Windows emulator like Parallels. Knowledgeable Mac and Linux users have also been known to successfully run UCINET on WINE, but the instructor is a Windows user and will not be able to help you with this.


Pre-Workshop Reading

To prepare for the seminar, the instructor recommends reading his book on network analysis, which is available on Amazon. Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing social networks. SAGE Publications Limited.


LOCATIONS, FORMAT, AND MATERIALS 

The seminar meets Friday, April 28 and Saturday, April 29 at Temple University Center City, 1515 Market Street, Philadelphia, PA 19103. 

The class will meet from 9 to 5 each day with a 1-hour lunch break. 

Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking. 


Registration and Lodging

The fee of $995.00 includes all seminar materials. The early registration fee of $895 is available until March 28. 

Refund Policy
If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50). 

Lodging Reservation Instructions

A block of guest rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut Street, Philadelphia, PA at a special rate of $154 per night. This location is about a 5 minute walk to the seminar location. In order to make reservations, call 203-905-2100 during business hours and identify yourself as part of the Statistical Horizons room block. For guaranteed rate and availability, you must reserve your room no later than Monday, March 27, 2017.

If you make reservations after the cut-off date ask for the Statistical Horizons room rate (do not use the code) and they will try to accommodate your request.


Seminar outline

  • The network perspective
    1. History of the field
    2. Key tenets
    3. Canonical research designs
  • Network data
    1. Importing survey data into UCINET
    2. Common data manipulations
    3. Visualizing networks
  • Node-level analysis
    1. Ego-network composition
    2. Structural holes and brokerage
    3. Centrality
  • Network-level analysis
    1. Network cohesion
    2. Network shape
    3. Detecting subgroups
  • Testing network hypotheses
    1. Introduction to permutation tests
    2. QAP correlation and regression

RECENT COMMENTS FROM PARTICIPANTS

“I found the instructor extremely clear in explaining difficult topics and very open to questions. We were able to cover a great deal of material in-depth over the two days. I feel much better prepared to use social network analysis in my own work.”
  Kevin McClure, University of North Carolina

“Very good course. I am new to the subject of social network analysis, and this course has given me a solid foundation to build on.”
  Andrew Tracy, University of Colorado

“Dr. Borgatti is a patient, friendly, and knowledgeable instructor who makes social network concepts accessible.”
  Michael S. Amato, Truth Initiative

“I liked this workshop for a wide range of applications that were demonstrated. The instructor was very helpful in answering questions as material was introduced, as well as willing to repeat demonstrations at certain points of confusion when learning how to use the software.”
  Natalia Vorotyntseva, University of Connecticut

“This course was excellent – a great introduction to social network analysis that integrated the theoretical perspective with practical concerns and hands-on application to data.”
  Anonymous

“After this workshop I already have several ideas for how to apply it to my data. Quite relevant!”
  Evgenia Valuy, Institute of International Education

“This course was interactive and hands-on, which will be very helpful as I use my own data in the future. You learn both concepts and procedures. Steve is very approachable and willing to explain things very simply.”
  Sarah Weiner, North Carolina State University/USDA

“This was a great introduction to the topic, blending theoretical approach and hands-on execution, by a very knowledgeable and enthusiastic instructor!”
  Abby Braitman, Old Dominion University