What's the distribution of centrality?
Recall that there are many ways that you can assess centrality of a graph. We will use two different methods you learned earlier: betweenness and eigen-centrality. Remember that betweenness is a measure of how often a given vertex is on the shortest path between other vertices, whereas eigen-centrality is a measure of how many other important vertices a given vertex is connected to. Before we overlay centrality on our graph plots, let's get a sense of how centrality is distributed.
Note that due to algorithmic rounding errors, we can't check for eigen-centrality equaling a specific value; instead, we check a range.
Deze oefening maakt deel uit van de cursus
Case Studies: Network Analysis in R
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Calculate directed betweenness of vertices
retweet_btw <- betweenness(___, directed = ___)
# Get a summary of retweet_btw
summary(___)
# Calculate proportion of vertices with zero betweenness
mean(___ == 0)