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

Federico Cinus, Marco Minici, Luca Luceri, Emilio Ferrara

Track: Social networks and social media

Keywords: Social media, Coordination detection

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 suspiciously similar sharing behaviors within and across platforms. Introducing 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.

Submission Number: 2090