This is a repository for the notebook I have prepared for this year's (2016) NTU Winter School on Complexity Science. The notebook is a supplementary material to Michael Lees and Debraj Roy's A Short Practical Introduction to NetworkX. The recipe is also the hands-on counterpart of the lecture I have prepared titled "Community Structures".

Real-world networks reveal clustering behaviour, which is exhibited in the formation of communities/clusters/partitions (used interchangeably in the recipe) in the graph structure. When studying networks, their structure and function, it is also crucial to identify these bunchings. Here, we explore these different structures with a strong focus on clustering and community detection. In particular, we look at two general methods, and three submethods:

1. Divisive Method

• Girvan-Newman Algorithm (using edge betweenness)

2. Agglomerative Method

• Hierarchical clustering (using a distance matrix)
• Louvain Algorithm (using modularity for optimization)