Take the Twitter graph you generated in question #1 and test for male-female homophily. For the purposes of this question you can consider the graph as undirected (i.e., no distinction between "follows" and "following"). Use the twitter name (not "screen name"; for example "Michael L. Nelson" and not "@phonedude_mln") and programatically determine if the user is male or female. Some sites that might be useful:
https://genderize.io/ https://pypi.python.org/pypi/gender-detector/0.0.4
Create a table of Twitter users and their likely gender. List any accounts that can't be determined and remove them from the graph.
Perform the homophily test as described in slides 11-15, Week 7.
Does your Twitter graph exhibit gender homophily?