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.
