Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election

Abstract

Coordinated information operations remain a persistent challenge on social media, despite platform efforts to curb them. While previous research has primarily focused on identifying these operations within individual platforms, this study shows that coordination frequently transcends platform boundaries. Leveraging newly collected data of online conversations related to the 2024 U.S. Election across $\mathbb{X}$ (formerly, Twitter), Facebook, and Telegram, we construct similarity networks to detect coordinated communities exhibiting suspicious sharing behaviors within and across platforms. Proposing an advanced coordination detection model, we reveal evidence of potential foreign interference, with Russian-affiliated media being systematically promoted across Telegram and $\mathbb{X}$. Our analysis also uncovers substantial intra- and cross-platform coordinated inauthentic activity, driving the spread of highly partisan, low-credibility, and conspiratorial content. These findings highlight the urgent need for regulatory measures that extend beyond individual platforms to effectively address the growing challenge of cross-platform coordinated influence campaigns.

HUMANS Lab -- Working Paper No. 2024.7 -- The 2024 Election Integrity Initiative -- University of Southern California - Updated Version of WWW '25 Submission

References in corpus (6)

• Propaganda and Misinformation on Facebook and Twitter during the Russian Invasion of Ukraine
• A General Method to Find Highly Coordinating Communities in Social Media through Inferred Interaction Links
• The Spread of Propaganda by Coordinated Communities on Social Media
• Temporal Dynamics of Coordinated Online Behavior: Stability, Archetypes, and Influence
• Exposing Influence Campaigns in the Age of LLMs: A Behavioral-Based AI Approach to Detecting State-Sponsored Trolls
• The influence of coordinated behavior on toxicity

Cited by in corpus (2)

• Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior
• Emergent Coordinated Behaviors in Networked LLM Agents: Modeling the Strategic Dynamics of Information Operations