roza / pydata_bcn_NetworkX

Materials for the NetworkX workshop at PyData Barcelona 2017 conference

Social Network Analysis with Python and NetworkX

Materials for the PyData Barcelona 2017 workshop on Network Analysis with Python and NetworkX.

Abstract

Social Network Analysis (SNA) has a wide applicability in many scientific fields and industries. This workshop is a gentle introduction to SNA using Python and NetworkX, a powerful and mature python library for the study of the structure, dynamics, and functions of complex networks. Participants in this workshop should have a basic understanding of Python, no previous knowledge of SNA is assumed.

For this workshop attendees will need to install NetworkX (>=1.11), Matplotlib (>=1.5), numpy (>=1.10) and have a working Jupyter Notebook environment. Some examples will also use Pandas (>=0.17) and Seaborn (>=0.7), but these packages are not essential. Only basic Python knowledge is assumed.

Outline of the workshop

1. Brief Introduction to Graph Theory

   • Mathematical foundation of Social Network Analysis.
   • Why graphical representations usually doesn't help much.

2. Creating and Manipulating Graphs

   • Data Structures: Graphs, DiGraphs, MultiGraphs and MultiDiGraphs.
   • Adding nodes and edges.
   • Adding and updating node and edge attributes.
   • Graph generators.
   • Visualizing graphs using Matplotlib.
   • Common formats for reading and writing Graphs.

3. Network Analysis

   • Basic concepts: Degree.
   • Distance measures: paths, simple paths, and shortest paths.
   • Node centrality analysis: measures and their relation.
   • Analyzing groups and subgroups: Cliques, k-cores, components, and k-components.

4. Bipartite Graphs

   • Definition of bipartite networks and their use in modeling group affiliations.
   • Working with bipartite networks with NetworkX.