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- ─── M01: Euler Path ───
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- ─── M02: Small World ───
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- ─── M04: Friendship Paradox ───
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- ─── M05: Clustering ───
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- ─── M06: Centrality ───
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- ─── M07: Random Walks ───
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- ─── M08: Embedding ───
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- ─── M09: Graph Neural Networks ───
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Advanced Topics in Network Science

Author

Sadamori Kojaku

Published

July 27, 2025

1 Module 5: Clustering

1.1 What to learn in this module

In this module, we will learn community detection, one of the most widely-used yet controversial techniques in network analysis. We will learn: - What is community structure in networks? - How to operationalize community structure? - How to find communities in networks? - Limitations of community detection - Keywords: community detection, assortativity, modularity, resolution limit, rugged landscape, random graph, label switching algorithm, Louvain algorithm, stochastic block model, the configuration model.

# Module 5: Clustering

## What to learn in this module

In this module, we will learn community detection, one of the most widely-used yet controversial techniques in network analysis. We will learn:
- What is community structure in networks?
- How to operationalize community structure?
- How to find communities in networks?
- Limitations of community detection
- **Keywords**: community detection, assortativity, modularity, resolution limit, rugged landscape, random graph, label switching algorithm, Louvain algorithm, stochastic block model, the configuration model.