Using the Twitter API and Plotly with Python, I created a visualization of a recent #EdTechChat on Twitter, held on December 14. If you aren’t familiar with graph theory, the dots in this visualization are referred to as nodes or vertices. They represent the Twitter users that participated in the chat. The line segments connecting them are called edges and represent a relationship between two Twitter users: one user follows the other.
If you hover over a node, you’ll get information about it: the username, the number of followers and following (these counts refer only to the community of users that took part in this chat, so followers and “followees” that didn’t participate are excluded), and the betweenness centrality. That last number is a measure of the number of shortest paths in the graph that pass through a particular user. It is one possible way to measure the influence of a user within this community. Some of the most influential users in this community as measured by betweenness centrality include @teachintechgal, @KleinErin, @thomascmurray, and @EdSurge. Don’t miss out on the fact that this interactive plot allows you to zoom in and out as well on different regions of the graph.
I feel the methodology employed to generate this graph could be of interest to others. As such, I am publishing it to my GitHub account and have a couple more blog posts on this topic. In particular, I would love to find a school interested in using this method to give students an opportunity to do a graph theory exploration that would go beyond what they’d normally get from a textbook.