TY - GEN
T1 - Who let the trolls out? towards understanding state-sponsored trolls
AU - Zannettou, Savvas
AU - Caulfield, Tristan
AU - Setzer, William
AU - Sirivianos, Michael
AU - Stringhini, Gianluca
AU - Blackburn, Jeremy
N1 - Publisher Copyright: © 2019 Association for Computing Machinery.
PY - 2019/6/26
Y1 - 2019/6/26
N2 - Recent evidence has emerged linking coordinated campaigns by state-sponsored actors to manipulate public opinion on the Web. Campaigns revolving around major political events are enacted via mission-focused "trolls." While trolls are involved in spreading disinformation on social media, there is liffile understanding of how they operate, what type of content they disseminate, how their strategies evolve over time, and how they influence the Web's information ecosystem. In this paper, we begin to address this gap by analyzing 10M posts by 5.5K Twiter and Reddit users identified as Russian and Iranian state-sponsored trolls. We compare the behavior of each group of state-sponsored trolls with a focus on how their strategies change over time, the different campaigns they embark on, and differences between the trolls operated by Russia and Iran. Among other things, we nd: 1) that Russian trolls were pro-Trump while Iranian trolls were anti-Trump; 2) evidence that campaigns undertaken by such actors are influenced by real-world events; and 3) that the behavior of such actors is not consistent over time, hence detection is not straightforward. Using Hawkes Processes, we quantify the influence these accounts have on pushing URLs on four platforms: Twiter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab. In general, Russian trolls were more influential and efficient in pushing URLs to all the other platforms with the exception of /pol/ where Iranians were more influential. Finally, we release our source code to ensure the reproducibility of our results and to encourage other researchers to work on understanding other emerging kinds of state-sponsored troll accounts on Twifier.
AB - Recent evidence has emerged linking coordinated campaigns by state-sponsored actors to manipulate public opinion on the Web. Campaigns revolving around major political events are enacted via mission-focused "trolls." While trolls are involved in spreading disinformation on social media, there is liffile understanding of how they operate, what type of content they disseminate, how their strategies evolve over time, and how they influence the Web's information ecosystem. In this paper, we begin to address this gap by analyzing 10M posts by 5.5K Twiter and Reddit users identified as Russian and Iranian state-sponsored trolls. We compare the behavior of each group of state-sponsored trolls with a focus on how their strategies change over time, the different campaigns they embark on, and differences between the trolls operated by Russia and Iran. Among other things, we nd: 1) that Russian trolls were pro-Trump while Iranian trolls were anti-Trump; 2) evidence that campaigns undertaken by such actors are influenced by real-world events; and 3) that the behavior of such actors is not consistent over time, hence detection is not straightforward. Using Hawkes Processes, we quantify the influence these accounts have on pushing URLs on four platforms: Twiter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab. In general, Russian trolls were more influential and efficient in pushing URLs to all the other platforms with the exception of /pol/ where Iranians were more influential. Finally, we release our source code to ensure the reproducibility of our results and to encourage other researchers to work on understanding other emerging kinds of state-sponsored troll accounts on Twifier.
KW - Equity crowdfunding
KW - Investing
KW - Investment success
KW - Portfolio diversity.
KW - User retention
UR - https://www.scopus.com/pages/publications/85069463871
U2 - 10.1145/3292522.3326016
DO - 10.1145/3292522.3326016
M3 - Conference contribution
T3 - WebSci 2019 - Proceedings of the 11th ACM Conference on Web Science
SP - 353
EP - 362
BT - WebSci 2019 - Proceedings of the 11th ACM Conference on Web Science
PB - Association for Computing Machinery, Inc
T2 - 11th ACM Conference on Web Science, WebSci 2019
Y2 - 30 June 2019 through 3 July 2019
ER -