Botometer
(formerly BotOrNot)
Principal Investigators: Filippo Menczer & Alessandro Flammini (IUB Informatics)
Botometer, formerly called BotOrNot, is a machine-learning algorithm that rates how likely a Twitter account is to be a bot, based on tens of thousands of labeled examples. Twitter users can log in and check the Botometer scores for their followers and other Twitter users. Botometer does not retain any data other than the account ID, scores, and any feedback optionally provided by the user. Technical details on Botometer's features, training, machine learning model, and accuracy can be found in our peer-reviewed publications.
Botometer is one of many tools in Indiana University's Observatory on Social Media (OSoMe).
IUNI is a joint partner on Botometer, along with CNetS, and IUNI's IT team helped create the Botometer tool and continues to enhance it. Emilio Ferrara (former IUNI research scientist), Onur Varol (former IUB PhD student), and current IUB PhD students Clayton Davis and Kevin Yang were all critical in the development of Botometer.