Update: Detecting communities with a co-occurrence graph
Previous post From our previous post, we’ve discovered that the community detection algorithms were mainly grouping based on document/location. This time, we created a new weighted co-occurrence graph of all the people in all documents, similar to the Les Miserables…
Exploring Network Models
Previous post: Creating a Network Graph There are a number of definitions for what it means to belong to a community. Usually, people are involved in multiple communities, but they have stronger ties to a few of those communities because they know…
Creating a Network Graph
Previous Post: Data Processing with NLTK From the ccp_people.csv file, we built a simple social network using Gephi. This was originally a undirected graph where each edge represented a connection that two people were in the same document. We first calculated…