Michael W. Kearney implemented a classifier for Twitter bots. It’s called botornot:
Uses machine learning to classify Twitter accounts as bots or not bots. The default model is 93.53% accurate when classifying bots and 95.32% accurate when classifying non-bots. The fast model is 91.78% accurate when classifying bots and 92.61% accurate when classifying non-bots.
Overall, the default model is correct 93.8% of the time.
Overall, the fast model is correct 91.9% of the time.
You can enter Twitter accounts to see what the model projects here. It’s barebones, and I’m not sure what the curve represents, but it’s fun to poke at.
Tags: bot, machine learning, Twitter

Source: http://flowingdata.com/2018/03/15/bot-or-not-a-twitter-user-classifier/