6.4 Week 6 Activities

6.4.1 Readings

None. The textbook does not provide a specific introduction to centraly measures for a whole network.

But you’re encouraged to look back into example papers you selected in Week 3 to see whether you’ve developed any fresh understanding after diving deeper into these measures. Please share your findings with the class on Slack.

6.4.2 Compute Node-level Measures

Like last week, you can continue to use a dataset you have, either your own dataset or a public one. Track R

Search “centrality” on the igraph doc page. For example, you will find that betweenness(g) is the function for computing betweenness centrality. Apply these centrality functions on your dataset from Week 5. Tweak the parameters, such as directed, to see how the results might change. Share your findings on Slack. Track Gephi

Some of you have already played with Gephi’s Statistics panel in Week 4. For this week,

  • Check page 12 of this Gephi tutorial to see how centralities could be computed using Gephi. See Figure 6.1.
  • Toggle to Data Laboratory to see results of Gephi computations in the Data Table tab. For example, if you click on Network Diameter in the Statistics panel, a number of centrality measures (including betweenness centrality) will be saved in the Data Table. You can click on the header of each column to sort the Data Table. See Figure 6.2.
  • Share your findings on Slack.
Gephi Graph Overview.

FIGURE 6.1: Gephi Graph Overview.

Gephi Data Laboratory.

FIGURE 6.2: Gephi Data Laboratory.

Like earlier weeks, if you have any questions or ideas, share in corresponding channels on Slack. Enjoy a great week!