Using the Yelp dataset, I filtered the review data for Toronto, and then only the positive reviews (3-5 stars) to see if I could find some connections between businesses by connecting satisfied customers. With Gephi, I created a 2 degree ego network centered around user HikPdCQGk1mk5JsPjur7Nw (Anna) and partitioned it with modularity to try to get networks with the most connections. If I had a computer with more than 16gb of RAM, I would be able to get even better graphs.
The whole network looks really cool, but is too broad to get any real information:
But if we look at the smaller modularity segments, things get more interesting.
These people like to have a good time, going to concert halls, stadiums, theatres and drinking a lot of booze. And also going to a condom store and a fetish shop. Makes sense.
This one is very interesting, and shows the value of looking at a broad range of businesses instead of filtering in only restaurants. Here we can see popular tourist destinations Casa Loma, Toronto Island, and St. Lawrence Market, which people can reach by the TTC. In the future, it might actually be valuable to keep all the reviews for the transportation instead of just positive reviews.