The DARPA Twitter Bot Challenge
Abstract
A number of organizations ranging from terrorist groups such as ISIS to politicians and nation states reportedly conduct explicit campaigns to influence opinion on social media, posing a risk to democratic processes. There is thus a growing need to identify and eliminate "influence bots" - realistic, automated identities that illicitly shape discussion on sites like Twitter and Facebook - before they get too influential. Spurred by such events, DARPA held a 4-week competition in February/March 2015 in which multiple teams supported by the DARPA Social Media in Strategic Communications program competed to identify a set of previously identified "influence bots" serving as ground truth on a specific topic within Twitter. Past work regarding influence bots often has difficulty supporting claims about accuracy, since there is limited ground truth (though some exceptions do exist [3,7]). However, with the exception of [3], no past work has looked specifically at identifying influence bots on a specific topic. This paper describes the DARPA Challenge and describes the methods used by the three top-ranked teams.
Cite
@article{arxiv.1601.05140,
title = {The DARPA Twitter Bot Challenge},
author = {V. S. Subrahmanian and Amos Azaria and Skylar Durst and Vadim Kagan and Aram Galstyan and Kristina Lerman and Linhong Zhu and Emilio Ferrara and Alessandro Flammini and Filippo Menczer and Andrew Stevens and Alexander Dekhtyar and Shuyang Gao and Tad Hogg and Farshad Kooti and Yan Liu and Onur Varol and Prashant Shiralkar and Vinod Vydiswaran and Qiaozhu Mei and Tim Hwang},
journal= {arXiv preprint arXiv:1601.05140},
year = {2017}
}
Comments
IEEE Computer Magazine, in press