Educators Twitter Network

For my final project, I used Twitter’s REST API and a Twitter library for python, called twitter-python, to acquire the timelines of over 500 self-identified teachers on Twitter. I then used python to parse, extract, and structure the user timeline data for a visualization program. I was interested in seeing the ways in which teachers were engaging with one another online, so I used the mentions that each Twitter user made as a way to measure this. A mention, I would argue, is telling of engagement, as the user actively chooses an individual to include in their tweet, or directs the contents of their tweet at someone. The result of my data collection and structuring is a force-directed network visualization. The acquisition and structuring of my data took place over two separate python scripts, run from the command line. Before writing my scripts however, I had to gain access to the Twitter API by acquiring access keys and tokens. Once I had these two items, I was able to begin writing my scripts. I used a library that interacts with the Twitter API called twitter-python, as it was one of the few Twitter libraries for python that can get user timeline data. All of the Twitter handles whose timelines I was interested in acquiring were stored in a csv file, housed in the same directory as the rest of my python scripts.