3. Network Density
StatisticsGraph Density
Defined as the # of actual ties / # of potential ties
Scale is normalized:
0-----------------------.5---------------------------------1
Low density High density
Karate Club = .07 density
8. Degree Centrality
Statisticsaverage degree auto populates data
lab
In-degree (# links in)
Out-degree (# links out)
Degree (sum of in/out)
Karate club degree (top 5): ID 34, 1, 33, 3, 2
9. Eigenvector Centrality
Statistics Eigenvector centrality
autopopulates data lab
Nodal influence is relative to its neighbors
Karate club top 5: ID 1, 2 3, 24, 25
10. Closeness Centrality
Statistics Avg. path length Autopopulates
data lab
Sum of the length of the shortest paths between
the node and all other nodes
Karate club: (some of the top) ID 3, 2, 3, 14
11. Betweenness Centrality
Statistics Avg. path length Autopopulates
data lab
Measure of centrality based on the shortest
paths
Karate club: (top 5) ID 3, 32, 9, 29, 4
12. Local Measures
Community Structure
Clique
◦ All nodes are interconnected to all
others
Community Detection
Modularity
◦ High: dense intragroup, sparse
intergroup ties
◦ Karate club: .416
Jorge
Antonio Paulina
Gloria
Miguel
Gabriel
Teresa
13. Stuck?
Go to the Gephi Tutorials on their website
Use this cheat sheet to help you out:
http://www.clementlevallois.net/gephi/tuto/en
/gephi_cheat%20sheets_en.pdf