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Uncovering Coordinated Cross-Platform Information Operations Threatening the Integrity of the 2024 U.S. Presidential Election Online Discussion

Marco Minici, Luca Luceri, Federico Cinus, Emilio Ferrara

TL;DR

The findings underscore the critical role of developing computational models to scale up the detection of threats on large social media platforms, and emphasize the broader implications of these techniques to detect IOs across the wider Web.

Abstract

Information Operations (IOs) pose a significant threat to the integrity of democratic processes, with the potential to influence election-related online discourse. In anticipation of the 2024 U.S. presidential election, we present a study aimed at uncovering the digital traces of coordinated IOs on $\mathbb{X}$ (formerly Twitter). Using our machine learning framework for detecting online coordination, we analyze a dataset comprising election-related conversations on $\mathbb{X}$ from May 2024. This reveals a network of coordinated inauthentic actors, displaying notable similarities in their link-sharing behaviors. Our analysis shows concerted efforts by these accounts to disseminate misleading, redundant, and biased information across the Web through a coordinated cross-platform information operation: The links shared by this network frequently direct users to other social media platforms or suspicious websites featuring low-quality political content and, in turn, promoting the same $\mathbb{X}$ and YouTube accounts. Members of this network also shared deceptive images generated by AI, accompanied by language attacking political figures and symbolic imagery intended to convey power and dominance. While $\mathbb{X}$ has suspended a subset of these accounts, more than 75% of the coordinated network remains active. Our findings underscore the critical role of developing computational models to scale up the detection of threats on large social media platforms, and emphasize the broader implications of these techniques to detect IOs across the wider Web.

Uncovering Coordinated Cross-Platform Information Operations Threatening the Integrity of the 2024 U.S. Presidential Election Online Discussion

TL;DR

The findings underscore the critical role of developing computational models to scale up the detection of threats on large social media platforms, and emphasize the broader implications of these techniques to detect IOs across the wider Web.

Abstract

Information Operations (IOs) pose a significant threat to the integrity of democratic processes, with the potential to influence election-related online discourse. In anticipation of the 2024 U.S. presidential election, we present a study aimed at uncovering the digital traces of coordinated IOs on (formerly Twitter). Using our machine learning framework for detecting online coordination, we analyze a dataset comprising election-related conversations on from May 2024. This reveals a network of coordinated inauthentic actors, displaying notable similarities in their link-sharing behaviors. Our analysis shows concerted efforts by these accounts to disseminate misleading, redundant, and biased information across the Web through a coordinated cross-platform information operation: The links shared by this network frequently direct users to other social media platforms or suspicious websites featuring low-quality political content and, in turn, promoting the same and YouTube accounts. Members of this network also shared deceptive images generated by AI, accompanied by language attacking political figures and symbolic imagery intended to convey power and dominance. While has suspended a subset of these accounts, more than 75% of the coordinated network remains active. Our findings underscore the critical role of developing computational models to scale up the detection of threats on large social media platforms, and emphasize the broader implications of these techniques to detect IOs across the wider Web.
Paper Structure (13 sections, 13 figures, 3 tables)

This paper contains 13 sections, 13 figures, 3 tables.

Figures (13)

  • Figure 1: Distribution of user interactions
  • Figure 2: CoURL 10-core Similarity network built using our method luceri2024unmasking. The coordinated accounts we detected are highlighted in yellow.
  • Figure 3: Example of three suspicious $\mathbb{X}$ accounts with similar descriptions, account aesthetics, and links to the same external domain. Account usernames have been obscured for privacy reasons.
  • Figure 4: Media outlets that 15 users promote in their bio. We report a snapshot of meigsbarrett.com from the Internet Archive, as it is not reachable anymore. Interestingly, boveed.beehiiv.com links to an $\mathbb{X}$ account (@Boveedmedia) that is suspended at the time of writing (10-25-2024), and to the YouTube channel @MediaOpinion0, also promoted by other suspicious websites (cf. Fig. \ref{['fig:clone-websites']}(b)) and several $\mathbb{X}$ accounts in their profile description (cf.\ref{['fig:zoomin-sim-network']}).
  • Figure 5: Snapshots of two identical websites promoting biased narratives. Web Archive did not store the images for patriotvoice.site.
  • ...and 8 more figures