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Complex Networks

Lab 2

Introduction to iGraph in R.

  • loading and saving graphs
  • visualisation
  • synthethic graphs (ER, BA, WS)
  • nodes degree

Lab 3

Network metrics.

  • shortest path
  • network diameter
  • closeness
  • betweenness

Lab 4

Communities.

  • community detection (V. Blondel algorithm)
  • modularity metric
  • communities visualisation
  • dendrograms
  • karate club network

./docs/communities.png

Lab 5

Temporal networks.

  • networkDynamic
  • Streaming Classroom Interactions Dataset
  • edges dynamics
  • centrality dynamics
  • fwd and bkwd paths
  • animations

Lab 6

Multilayer networks.

  • multinet
  • metrics for multilayer networks
  • communities detection
  • distance metrics
  • loading/saving to file
  • evolving network
  • layers comparison
  • visualisation

Lab 7

Social influence

  • Linear Threshold model

./docs/linear_threshold.png

Lab 8

SIR Model

./docs/sir.png

Lab 9

SIR model with adaptive availability. Added parameter of availability of edges.

Lab 10

Concurrent processes on SIR model.

Lab 11

SIR model with pernament deletion of nodes.

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Complex Network course - 2020

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