Turing data science class: The practice of network analysis

Speaker: Bernie Hogan (Turing Fellow, University of Oxford)

Date: 13 November 2017

Time: 13:30 – 16:30

Registration: as this class will be in workshop style and due to limited space, the class is open for Turing students and researchers only.

Should this class be live streamed, you will be able to view it on our YouTube page


In this advanced class, we will be exploring how to analyse a social network. We will use networks of varying sizes from less than thirty people to several hundred and larger. We will be able to put in practice many of the concepts introduced in the prior class in order to describe social networks as forms of social structure. What is most interesting in most networks are not the dots and lines, but the micro-level practices that produce emergent macro-level phenomena.

To perform the analyses we will be using Python and Gephi. Source code and a walkthrough will be provided. Prior to class, students are encouraged to download both programs.

Readings:
iGraph Core Team (2016). iGraph Tutorial. Retrieved online from: http://igraph.org/python/doc/tutorial/tutorial.html

Newman, M. (2010) Chapter 7. Measures and metrics / Chapter 8. The large-scale structure of networks. In Networks: An Introduction. Oxford, UK: Oxford University Press. Pp. 168-272.