A research paper introduces a semi-automatic machine learning pipeline (SAMLP) called BotArtist for bot detection on Twitter.
SAMLP leverages nine publicly available datasets to train the BotArtist model.
BotArtist outperforms existing Twitter bot detection methods by almost 10% in terms of F1-score, achieving an average score of 83.19% and 68.5% over specific and general approaches, respectively.
The research provides one of the largest labeled Twitter bot datasets, containing features and BotArtist predictions for 10,929,533 Twitter user profiles.