These are a collection of scripts that allow you to apply the DBSCAN algorithm to a person's "Followed" list on Twitter.

get_followers.py and get_complete_follow_graph.py are for collecting the Twitter data, and process_data.jl is for processing it into clusters.

This project depends on the Python packages listed in requirements.txt. Install them system-wide or in a virtualenv.

The collection process takes 3 steps:

1. Run get_followers.py with three CLI arguments: the username of the account you wish to examine, your own Twitter username, and your Twitter password. Pipe the output of this into a file with a name of your choosing.
2. Run get_complete_follow_graph.py with three CLI arguments: the file where the output of step 1 is stored, your Twitter username, and your Twitter password. This collects the follow lists of everyone in your follow list and puts it in data/ folder.
3. Run process_data.jl with one CLI argument: the name of a data folder (data/ itself, or another folder if you've moved the output of step 2 somewhere else). This will output clusters.

• Workflow needs improvement
• Selenium script unable to operate in PhantomJS, so it annoyingly opens Firefox browser windows.