Social Network Analysis. MAGoLEGO course.

Spring 2015. Module 4

Department of Data Analysis and Artificial Intelligence, School of Computer Science.

Instructors: Prof. Leonid Zhukov, Dr. Ilya Makarov
Teaching assistant: Andrey Shestakov

Course wiki page: Magolego SNA 2015
Course page at cs.hse: Magolego Social Network Analysis

Course Outline

  1. Introduction to network science
  2. Descriptive network analysis
  3. Mathematical models of networks
  4. Node centrality and ranking on networks
  5. Network communities
  6. Network structure and visualization
  7. Social media and information flow in networks
  8. Social influence and decision making


  1. [03.04.2015] Introduction to network science. [Lecture 1] [Video]
    Introduction to network science. Examples.
  2. [10.04.2015] Descriptive network analysis. [Lecture 2] [Video]
    Basic graph theory notations. Node degree. Node degree distribution. Power laws. Scale free networks. Connected components. Graph diameter. Average path length. Local and global clustering coefficients. Transitivity.
  3. [17.04.2015] Mathematical models of networks. [Lecture 3][Video]
    Erdos-Reni random graph model. Bernoulli distribution. Phase transition, gigantic connected component. Diameter and cluster coefficient. Barabasi-Albert model. Preferential attachement. Small world model. Watts-Strogats model. Transition from regular to random
  4. [24.04.2015] Node centrality and ranking on networks. [Lecture 4] [Video]
    Node centrality metrics, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. Katz status index and Bonacich centrality, alpha centrality PageRank,Hubs and Authorites.
  5. [15.05.2015] Network communities [Lecture 5] [Video]
    Cohesive subgroups. Graph cliques. Network communities. Graph partitioning. Modularity. Edge Betweenness. Spectral partitioning. Modularity maximization. Heuristic methods. Label propagation. Fast community unfolding. Walktrap.
  6. [22.05.2015] Network structure and visualization [Lecture 6] [Video]
  7. k-core decomposition of networks. Diads and triads. Edge reciprocity. Frequent subgraphs. Network motifs. Assortative mixing. Network visualization. Forde directed layouts. Adjacency matrix ordering.
  8. [29.05.2015] Social media and information flow in networks [Lecture 7] [Video]
    Epidemic models on networks. SI, SIS, SIR models. Rumor spreading. Propagation trees.
  9. [05.06.2015] Diffusion of innovation [Lecture 8]
    Diffusion of innovation. Linear threshold model. Influence maximization.
  10. [26.06.2015] Exam

Labs & Homeworks

Available at Magolego SNA 2015

Reading material





SNA courses online