Botometer
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). Mac app store catalina download.
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.
Bot Detector Tf2
Description: DeBot is real-time bot detection system. The project started on Feb 2015 and it has been collecting data since Aug 2015. High correlation in activities among users in social media is unusual and can be used as an indicator of bot behavior. DeBot identifies such bots in Twitter network. Botometer is a machine learning algorithms that considers more than a thousand features about an account and its activity to estimate the likelihood that the account is automated. We consider accounts with bot score above a high threshold to identify content generated by likely social bots. How is the BEV calculated?
Visit: https://botometer.iuni.iu.edu
Botometer Api
Merih Angın
Merih Angın is an Assistant Professor at the International Relations Department of Koç University. Previously, she was a Postdoctoral Fellow at the Weatherhead Center for International Affairs of Harvard University, a postdoctoral research fellow at the Blavatnik School of Government of the University of Oxford, and a visiting scholar at the Mortara Center for International Studies of the Edmund A. Walsh School of Foreign Service at Georgetown University. Dr. Angın holds a PhD degree in International Relations/Political Science from the Graduate Institute of International and Development Studies (IHEID), an M.Sc. degree in International Relations from METU, and a Bachelor’s degree in Economics from Bilkent University. Her research interests lie in the areas of international political economy, international organizations, international development, international financial institutions, investment arbitration, political economy of privatization, migration, quantitative methods, agent-based modelling, machine learning, artificial intelligence and computational social sciences. Her research on IMF lending has recently been awarded the European Commission’s Marie Skłodowska-Curie Actions Individual Fellowship, as well as the Scientific and Technological Research Council of Turkey’s International Fellowship for Outstanding Researchers for 3 years.