TROLLMAGNIFIER: Detecting State-Sponsored Troll Accounts on Reddit
Not on the map. Why?
Abstract (arXiv)
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%.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Dec 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 2; 2023: 1; 2024: 4; 2025: 1; 2026: 2.
10 papers.
- 2022Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systemscited by 11
- 2022Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trollscited by 8
- 2023Specious Sites: Tracking the Spread and Sway of Spurious News Stories at Scalecited by 7
- 2024Enabling Contextual Soft Moderation on Social Media through Contrastive Textual Deviationcited by 2
- 2025Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websitescited by 1
- 2024SoMeR: Multi-View User Representation Learning for Social Mediacited by 0
- 2024PIXELMOD: Improving Soft Moderation of Visual Misleading Information on Twittercited by 0
- 2024Health Misinformation in Social Networks: A Survey of IT Approachescited by 0
- 2026Beyond Content: Behavioral Policies Reveal Actors in Information Operationscited by 0
- 2026Cross-National Information Attacks: A Two-Decade Analysis of Troll Behavior in Koreacited by 0
- 2026Cross-National Information Attacks: A Two-Decade Analysis of Troll Behavior in Korea22 Jun 2026
- 2026Beyond Content: Behavioral Policies Reveal Actors in Information Operations2 Feb 2026
- 2025Tracking the Takes and Trajectories of English-Language News Narratives across Trustworthy and Worrisome Websites15 Jan 2025
- 2024Health Misinformation in Social Networks: A Survey of IT Approaches24 Oct 2024
- 2024PIXELMOD: Improving Soft Moderation of Visual Misleading Information on Twitter30 Jul 2024
- 2024Enabling Contextual Soft Moderation on Social Media through Contrastive Textual Deviation30 Jul 2024
- 2024SoMeR: Multi-View User Representation Learning for Social Media2 May 2024
- 2023Specious Sites: Tracking the Spread and Sway of Spurious News Stories at Scale3 Aug 2023
- 2022Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls17 Oct 2022
- 2022Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systems7 Sep 2022