Introduction to Social Network Analysis
A 2-Day Seminar Taught by Stephen Borgatti, Ph.D.
To see a sample of the course materials, click here.
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.
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. Please download the 32-bit version only. The course is heavily hands-on, so you must bring a laptop with UCINET installed. Power outlets will be provided at each seat.
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.
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.
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.
LOCATION, FORMAT AND MATERIALS
The class will meet from 9 am to 5 pm each day with a 1-hour lunch break at Temple University Center City, 1515 Market Street, Philadelphia, PA 19103.
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 27.
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 $159 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 by using group code SH0426 or click here. For guaranteed rate and availability, you must reserve your room no later than Monday, March 26, 2018.
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.
- The network perspective
- History of the field
- Key tenets
- Canonical research designs
- Network data
- Importing survey data into UCINET
- Common data manipulations
- Visualizing networks
- Node-level analysis
- Ego-network composition
- Structural holes and brokerage
- Network-level analysis
- Network cohesion
- Network shape
- Detecting subgroups
- Testing network hypotheses
- Introduction to permutation tests
- QAP correlation and regression
“Dr. Borgatti provides a fresh and informative course on social network analysis. He provides a great balance of lecture and application. The course is perfect for those who are beginning to learn social network analysis.”
David Hurtado, Oregon Health and Science University
“This course was a great experience. I benefitted the most from the amount of knowledge and experience Dr. Borgatti has. He could answer any question and was even happy to think about the more challenging ones. Dr. Borgatti has a good sense of humor, which helped me concentrate and kept me motivated.”
Sophie Urmetzer, University of Hohenheim
“This was a great introduction course and overview of social network analysis. The course had a good combination of theory and hands-on activities. Overall, I had a very nice experience.”
Bian Liu, Icahn School of Medicine at Mount Sinai
“I knew very little about social network analysis. After attending this workshop, I can affirm that I have a broader understanding of social network analysis and its applications. Now, I should be able to conceptualize projects in dental public health and health sources research.”
Vinodh Bhoopathi, Temple University, Maurice H. Kornberg School of Dentistry
“This course was an effective overview of the broad swath of SNA theory and methods. It was very helpful to practice the application of a concept during the course.”
Andrew Akin, U.S. Air Force, Air Command and Staff College
“This course was an excellent introduction to the foundation of social network concepts and software. The instructor was truly wonderful. He was approachable, engaging, and well-paced. He responded well to participants of all learning levels.”
Mariya Petrova, University of Miami
“Dr. Borgatti is a very knowledgeable person. His examples on social network analysis were thorough and complete. The atmosphere of the class was fantastic. You can feel free to ask any questions. After the first sessions of the course, I asked Dr. Borgatti questions about my project. He gave me ideas and helped me to come up with new methods.”
Mansoor Shekarian, North Carolina Agricultural and Technical State University
“This was a great introduction to social network analysis course. I learned so much in just 2 days.”
Preethy George, Westat
“As an undergraduate sociology major, Steve’s course helped introduce me to SNA and helped me understand its application within sociology and health. The course is a great balance of theory and practice, with relatively deep exposure to multiple important topics.”
Elena Diller, Washington and Lee University
“If you are looking for a social network analysis class, this is the class! Dr. Borgatti is very organized, knowledgeable, and responsible. You will learn a lot during this 2-day workshop.”
Heeyoung Jung, Temple University
“As a PhD student in business school, this class provided both practical and theoretical foundation in social network. I would recommend this course to all PhD students who are familiar with the topic but not clear on how to perform the research. You will learn so much from discussing your ideas with Steve.”
“This course is perfect for those with beginner to intermediate knowledge in social network analysis. I have been using UCINET for a year and found this course extremely helpful. It was a review of social network theory for me, and also helped stimulate new ideas for analyzing my data.”
Avrum Gillespie, Temple University, Lewis Katz School of Medicine