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

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 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 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.

Authors

Institutions

Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1145/3696410.3714698
Citations
6
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
23.18

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Marco Minici, Emilio Ferrara, Luca Luceri, Federico Cinus
6 citations
Social Media and Politics
23.18
article

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

Marco Minici, Emilio Ferrara, Luca Luceri, Federico Cinus
article en
6 citations

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 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 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.

University of Pisa (IT), University of Southern California (US)
Defense Advanced Research Projects Agency
Openalex Percentile: Top 1%
Social Media and Politics
23.18
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.