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arXiv · 1601.05140

The DARPA Twitter Bot Challenge

V. S. Subrahmanian·Amos Azaria·Skylar Durst·Vadim Kagan·Aram Galstyan·Kristina Lerman·Linhong Zhu·Emilio Ferrara·Alessandro Flammini·Filippo Menczer·Andrew Stevens·Alexander Dekhtyar·Shuyang Gao·Tad Hogg·Farshad Kooti·Yan Liu·Onur Varol·Prashant Shiralkar·Vinod Vydiswaran·Qiaozhu Mei·Tim Hwang
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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.

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V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, Vinod Vydiswaran, Qiaozhu Mei, Tim Hwang. 2016-01-20. The DARPA Twitter Bot Challenge. https://doi.org/10.1109/mc.2016.183

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