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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

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Exercise instructions

  • Compute the betweenness centrality bet_cen of the nodes in the graph T.
  • Compute the degree centrality deg_cen of the nodes in the graph T.
  • Compare betweenness centrality to degree centrality by creating a scatterplot of the two, with list(bet_cen.values()) on the x-axis and list(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()
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