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WACC Workshop

Social Network Analysis: Principles and Applications

by Petr Matous

Download PPT slides

This workshop introduces the most basic concepts and methods of Social Network Analysis. It comprises two sessions.

The first session explains principle concepts such as centrality (i.e., who is important in a network). Without using advanced mathematics, the intuitive meaning of the SNA concepts will be demonstrated on the social network of offline interactions among the workshop participants. This exercise will also serve to highlight some challenges in social network data gathering. No prior background knowledge is expected for participation in the first session.

In the second session, the participants will learn to visualize and explore their online networks, using data from Facebook. Example of the application of the introduced methods in previous studies will also be shown. Time will be reserved for discussions. Participation in only one of the two sessions is possible.

Workshop Overview

(31 October, 2014)

Morning session: Background information

Afternoon session: network visualization and research examples
11.00 - 12.45, room H0.58 14.30 - 16.15, room R0.03/4
  • Elements of networks (demonstrated on a network among the participants)
  • Principles of network formation
  • Whole network versus personal networks
  • Network surveys
  • Measuring social capital Interventions on dynamic networks
  • Network diffusion
  • Networks and technologies
  • Online networks Networks in the workplace
  • Discussing the application of SNA to the participants’ own research

About the instructor

Petr Matous is an Associate Professor in the School of Engineering, University of Tokyo where he teaches Social Network Analysis to graduate engineering students. petr_matous


(Unfortunately, the maximum number of registrations was reached.

We might be able to offer this workshop again if there sufficient interest in it. If you would like to attend this workshop at some other time, please get in touch with Daniel Dauber,

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Thank you for your time.