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.
Este exercício faz parte do curso
Introduction to Network Analysis in Python
Instruções do exercício
- Compute the betweenness centrality
bet_cen
of the nodes in the graphT
. - Compute the degree centrality
deg_cen
of 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.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# 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()