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Lecture 1: SNA 0 of 21 activities solved
  1. 0. Network packages in R
  2. 1.1. Simple descriptives - Network size
  3. 1.2. Simple descriptives - Density and components
  4. 1.3. Simple descriptives - Diameter and clustering coefficient
  5. 1.4 Network Descriptives Cheatsheet
  6. 2.1. Network representation via statnet - Starting from the adjacency matrix
  7. 2.2. Network representation via statnet - Starting from the edgelist
  8. 2.3. Network representation via statnet - Set node attributes
  9. 2.4. Network representation via statnet - Set tie attributes
  10. 2.5. Network representation via igraph - Starting from the adjacency matrix
  11. 2.6. Network representation via igraph - Starting from the edgelist
  12. 3. Network visualisation
  13. 4. Centrality measures - Degree, closeness and betweenness
  14. 5.1. Network clustering
  15. 5.2. Network clustering - The behavior of Q
  16. 6.1. Homophily - Data and Network creation
  17. 6.2. Homophily - Network Plotting
  18. 6.3. Homophily - Network Properties
  19. 6.4. Homophily - Heterophilicity
  20. 6.5. Homophily - Dyadicity
  21. 7. Graph representation learning
Lecture 1: SNA

6.2. Homophily - Network Plotting

This course is archived, so you can no longer hand in solutions.

names <- c('Tom', 'Sofie', 'Karen', 'Arno', 'Jan', 'Laura') master <- c('B', 'E', 'B', 'E', 'E', 'B') Students <- data.frame(name = names, master = master)