Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916704490094592 |
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| author | Cinus, Federico Minici, Marco Luceri, Luca Ferrara, Emilio |
| author_facet | Cinus, Federico Minici, Marco Luceri, Luca Ferrara, Emilio |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_22716 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election Cinus, Federico Minici, Marco Luceri, Luca Ferrara, Emilio Social and Information Networks 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. |
| title | Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2410.22716 |