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README

NetPy '19: Introduction to Network Analysis in Python

Workshop instructor

Asst. Prof. Lovro Šubelj, PhD, University of Ljubljana

Workshop schedule

Tuesday, 10th December 2019 at 3:30 PM (4 hours with breaks)

Workshop location

Lecture room 3 at UL FRI, Večna pot 113, Ljubljana, Slovenia

Materials and forum
High-level description

The workshop is primarily aimed at Python programmers, either academics, professionals or students, that wish to learn the basics of modern network science and practical analyses of complex real networks, such as social, information and biological networks. Familiarity with the basics of probability theory, statistics and linear algebra is strongly encouraged. The workshop is based on masters level course Network Analysis offered at University of Ljubljana, Faculty of Computer and Information Science.

Recommended prerequisites

It is recommended that attendees bring a laptop with working installation of Python, NetworkX and CDlib packages, and necessary dependencies. Alternatively, you can work with any other network analysis package such as igraph, graph-tool or SNAP.py. Finally, for the purposes of visualization of smaller networks, it is recommended to have working installation of some network analysis software such as Gephi or visone.

Tentative syllabus
  1. From classical graph theory to modern network science (30 min)
  2. Large-scale structure of real networks and graph models (50 min)
  3. Measures of node importance and link analysis algorithms (50 min)
  4. Network community, core-periphery and other structures (50 min)
  5. Network-based mining, visualization and some applications (50 min)

Networks data

All networks are available in Pajek, edge list in LNA formats.

Let's start with Guimera's four knights challenge

Tentative duration

5+5 min

Challenge description

To be revealed in class =)

4knights

1. Classical graph theory → modern network science

Tentative duration

20+10 min

Brief description

Introduction of networks and selected motivational examples. From classical graph theory to social network analysis and modern network science. Network perspectives in different fields of science.

transportation

Lecture slides
Book chapters
Selected must-reads
Selected papers

2. Large-scale network structure and graph models

Tentative duration

30+20 min

Brief description

Classical graph theory and modern network analysis. Random graphs, scale-free and small-world network models, and real network structure. Network representations, data formats and repositories.

smallworld

Lecture slides
Hands-on analysis
Networks data
Book chapters
Selected must-reads
Selected papers

3. Measures of node importance and link analysis

Tentative duration

30+20 min

Brief description

Node importance and measures of centrality, i.e. clustering coefficients, spectral, closeness and betweenness centrality, and link analysis algorithms. Link importance and measures of bridging, i.e. betweenness centrality, embeddedness and topological overlap.

centrality

Lecture slides
Hands-on analysis
Networks data
Book chapters
Selected must-reads
Selected papers

4. Clusters of nodes and network mesoscopic structure

Tentative duration

30+20 min

Brief description

Network community, core-periphery and other mesoscopic structures. Graph partitioning, community detection, blockmodeling, stochastic block models and core-periphery detection.

community

Lecture slides
Hands-on analysis
Networks data
Book chapters
Selected must-reads
Selected papers

5. Network-based mining, visualization and applications

Tentative duration

30+20 min

Brief description

Network-based node clustering, classification and regression. Force-directed node layout and network visualization. Selected applications of network analysis (i.e. automobile insurance fraud and historical development of science).

collisions

Lecture slides
Hands-on analysis
Networks data
Selected must-reads
Selected papers