The DARPA Twitter Bot Challenge
| Autor: | Subrahmanian, V. S., Azaria, Amos, Durst, Skylar, Kagan, Vadim, Galstyan, Aram, Lerman, Kristina, Zhu, Linhong, Ferrara, Emilio, Flammini, Alessandro, Menczer, Filippo, Stevens, Andrew, Dekhtyar, Alexander, Gao, Shuyang, Hogg, Tad, Kooti, Farshad, Liu, Yan, Varol, Onur, Shiralkar, Prashant, Vydiswaran, Vinod, Mei, Qiaozhu, Hwang, Tim |
|---|---|
| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | Computer 49 (6), 38-46. IEEE, 2016 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/MC.2016.183 |
| Popis: | 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. Comment: IEEE Computer Magazine, in press |
| Databáze: | arXiv |
| Externí odkaz: |
|