Betweenness centrality
Betweenness centrality for retweet and reply networks signals users who bridge between different Twitter communities. These communities may be tied together by topic or ideology.
networkx has been imported as nx.
The networks G_rt and G_reply, and column_names = ['screen_name', 'betweenness_centrality'] have been loaded for you.
This exercise is part of the course
Analyzing Social Media Data in Python
Exercise instructions
- Calculate betweenness centrality for the retweet network using
nx.betweenness_centrality(). - Do the same for the reply network.
- Create a DataFrame out of retweet centralities.
- Do the same for the reply network.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Generate betweenness centrality for retweets
rt_centrality = ____
# Generate betweenness centrality for replies
reply_centrality = ____
# Store centralities in data frames
rt = pd.DataFrame(____, ____ = ____)
reply = pd.DataFrame(____, ____ = ____)
# Print first five results in descending order of centrality
print(rt.sort_values('betweenness_centrality', ascending = False).head())
# Print first five results in descending order of centrality
print(reply.sort_values('betweenness_centrality', ascending = False).head())