Universidade Federal do Rio Grande do Norte

Instituto Metrópole Digital

IMD1155 - Network Analysis

References

📚 Menczer, Filippo; Fortunato, Santo; A. Davis, Clayton. A First Course in Network Science [Link]
📚 Dmitry Zinoviev. Complex Network Analysis in Python [Link]
📚 Coscia, Michele. The Atlas for the Aspiring Network Scientist [Link]
📚 Mark Newman. Networks. [Link]
🔥 Literature of Deep Learning for Graphs [Link]
📣 A scientific network data repository [Link]
🔖 Stanford large network dataset collection (SNAP) [Link]

Lessons

Week 01
- Course Outline & Syllabus
- Data Science vs Graph Data Science
- Historical Context of Network Analysis
- Google Colab Introduction
- Google Colab Cont.
- Further studies
Week 02 Network Elements
- Outline
- Basic Definitions
- Extended Graphs
- Density, Sparsity and Subnetworks
- Degree and Network Representation
- Further Reading
- NetworkX
- Graph-Tool
Week 03 Exercise
Week 04 Small Worlds
- Outline
- Assortativity
- Paths, Walks and Distances
- Connected Components
- Clustering Coefficient
Week 05 Exercise
Week 06 Hubs
- Outline
- Eccentricity, Diameter, Periphery, Radius and Center
- Degree, Closeness, Betweenness and Eigenvector Centrality
- Centrality Distributions Part 01
- Centrality Distributions Part 02
- Core Decomposition Part 01
- Core Decomposition Part 02
- Hands on hubs
Week 07 Directed networks: case study of Wikipedia pages
- Building a networking from Wikipedia pages
- Collecting data from a snowballing process
- Truncate and eliminate duplicates
- Exploring the network
- Gephi
  - Install
  - Quick start
  - Using layouts
  - Node and network measures
  - Visualize and filter
  - Renderize and export
  - Highlighting a community
  - Deploy the network [Page link]
Week 08 Directed networks: case study of Twitter
- Get started with Twitter APIs and tools
- Authenticating with Twitter's API
- Twitter API basics
- Using Twitter's search API to get tweets of interest
- Twitter retweet network
- Twitter mention network