Social network analysis

Introduction to Social Network Analysis

Wednesday, 14:45 – 16:30
This session will provide an introduction to Social Network Analysis by overviewing its development starting with its intellectual origins and culminating with its recent ascendance as one of the most innovative approaches being adopted by humanists and social scientists.

Descriptive Network Analytics

Wednesday, 17:00 – 19:00
This session will begin by defining various properties of a network: its nodes and relations. Next the session will describe metrics to describe individual nodes in a network. The session will conclude with a description of metrics to describe parts of and/or the whole network.

Predictive Network Analytics

Thursday, 09:00 – 10:00
This session will introduce recent techniques to go beyond describing a network to predicting it. This helps us to better understand the emergence and consequences of network formation. Specifically this session will provide a brief (mostly non-technical) overview of Quadratic Assignment Procedure (QAP), Exponential Random Graph Models (ERGMs), Stochastic Actor Oriented Models (SAOM), and Relational Event Models (REM).

Leveraging Computational Social Science to address Grand Societal Challenges

Thursday, 10:00 – 11:15
The increased access to big data about social phenomena in general, and network data in particular, has been a windfall for social scientists. But these exciting opportunities must be accompanied with careful reflection on how big data can motivate new theories and methods. This session will use examples of Contractor’s research, in the area of SNA, to demonstrate that Computational Social Science serves as the foundation to unleash the intellectual insights locked in big data. More importantly, he will illustrate how these insights offer social scientists in general, and social network scholars in particular, an unprecedented opportunity to engage more actively in monitoring, anticipating and designing interventions to address grand societal challenges.

Computational analyses on network data

Thursday, 13:30 – 15:30, 16:00 – 18:00
In the lab sessions we will use software tools to analyze network data, where we will give equal emphasis to conducting the analysis and interpreting the results. We will focus on the following social network analysis tools:

  • Gephi: an interactive visualization and exploration tool for all kinds of networks and complex systems, dynamic and hierarchical graphs (runs on Windows, Linux and Mac)
  • NodeXL: a free, open-source template for Microsoft Excel that makes it easy to explore network graphs. NodeXL requires Office 2007, 2010 or 2013. Mac users can run NodeXL in a virtual machine locally or in the cloud.

Install both of them if possible. However, there will be a stronger focus on Gephi, so if you are not a Windows user and have problems to install NodeXL, no worries you can team up with a Windows user for the NodeXL exercise.

Recommended Readings:
  • Lazer, D., et al. (2009). “Life in the network: the coming age of computational social science” Science (New York, NY), 323(5915), 721.
  • Marin, A. & Wellman, B. (2010). “Social Network Analysis: An Introduction” Carrington, P. & Scott, J. (eds), Handbook of Social Network Analysis, London: Sage.
  • Monge, P.R. & Contractor, N. S. (2003). “Multitheoretical, Multilevel Models of Communication and Other Organizational Networks” Ch. 10 in Theories of Communication Networks, New York: Oxford University Press.

You can download the PDFs here (password required).