NetworkX betweenness centrality on a social network
Betweenness centrality is a node importance metric that uses information about the shortest paths in a network. It is defined as the fraction of all possible shortest paths between any pair of nodes that pass through the node.
NetworkX provides the nx.betweenness_centrality(G) function for computing the betweenness centrality of every node in a graph, and it returns a dictionary where the keys are the nodes and the values are their betweenness centrality measures.
This exercise is part of the course
Introduction to Network Analysis in Python
Exercise instructions
- Compute the betweenness centrality
bet_cenof the nodes in the graphT. - Compute the degree centrality
deg_cenof the nodes in the graphT. - Compare betweenness centrality to degree centrality by creating a scatterplot of the two, with
list(bet_cen.values())on the x-axis andlist(deg_cen.values())on the y-axis.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Compute the betweenness centrality of T: bet_cen
bet_cen = ____
# Compute the degree centrality of T: deg_cen
deg_cen = ____
# Create a scatter plot of betweenness centrality and degree centrality
____
# Display the plot
plt.show()