TrollMagnifier: Detecting State-Sponsored Troll Accounts on Reddit

Mohammad Hammas Saeed, Shiza Ali, Jeremy Blackburn, Emiliano De Cristofaro, S. Zannettou, Gianluca Stringhini

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

13 Citations (Scopus)
225 Downloads (Pure)

Abstract

Growing evidence points to recurring influence campaigns on social media, often sponsored by state actors aiming to manipulate public opinion on sensitive political topics. Typically, campaigns are performed through instrumented accounts, known as troll accounts; despite their prominence, however, little work has been done to detect these accounts in the wild. In this paper, we present TROLLMAGNIFIER, a detection system for troll accounts. Our key observation, based on analysis of known Russian-sponsored troll accounts identified by Reddit, is that they show loose coordination, often interacting with each other to further specific narratives. Therefore, troll accounts controlled by the same actor often show similarities that can be leveraged for detection. TROLLMAGNIFIER learns the typical behavior of known troll accounts and identifies more that behave similarly. We train TROLLMAGNIFIER on a set of 335 known troll accounts and run it on a large dataset of Reddit accounts. Our system identifies 1,248 potential troll accounts; we then provide a multi-faceted analysis to corroborate the correctness of our classification. In particular, 66% of the detected accounts show signs of being instrumented by malicious actors (e.g., they were created on the same exact day as a known troll, they have since been suspended by Reddit, etc.). They also discuss similar topics as the known troll accounts and exhibit temporal synchronization in their activity. Overall, we show that using TROLLMAGNIFIER, one can grow the initial knowledge of potential trolls provided by Reddit by over 300%.
Original languageEnglish
Title of host publicationProceedings - 43rd IEEE Symposium on Security and Privacy, SP 2022
PublisherIEEE
Pages2161-2175
Number of pages15
ISBN (Electronic)9781665413169
DOIs
Publication statusPublished - 2022
Event43rd EEE Symposium on Security and Privacy (SP) - San Francisco, United States
Duration: 22 May 202226 May 2022
Conference number: 43
https://www.ieee-security.org/TC/SP2022/

Conference

Conference43rd EEE Symposium on Security and Privacy (SP)
Country/TerritoryUnited States
CitySan Francisco
Period22/05/2226/05/22
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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