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Alexandros Efstratiou @alextheefstra.eurosky.social · 19/03/2026

Peaks in superspreader activity tend to precede peaks in media activity; suggests that conversations take place on Twitter before they are picked up by the news, but this is by no means a strict causal pathway

A figure showing a precedence network between contrarian superspreaders, conformist superspreaders, low-trust news outlets, and high-trust news outlets. Both types of superspreaders precede both types of news most of the time. News outlets typically only precede each other.

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Alexandros Efstratiou @alextheefstra.eurosky.social · 19/03/2026

There is some crossover in the activity of superspreaders and news media. Looking at superspreader-media outlet neighbors (where neighbors = share similar papers), conformist superspreaders align with mainstream media; contrarians align with pseudoscience/conspiratorial media

Violin plot that shows the kinds of media outlet neighbors for conformist and contrarian superspreaders. Whereas conformists mostly align with high-trust, mainstream media outlets, contrarians mostly share similar papers with low-trust media outlets, including pseudoscientific and conspiratorial outlets.

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Alexandros Efstratiou @alextheefstra.eurosky.social · 19/03/2026

Around ~20% of superspreaders are COVID contrarians. The coordinated network we detect retweets these contrarians almost exclusively (many are also MDs, scientists, etc). Further analyses show that the coordinated accounts are not bots, but difficult to ascribe intent beyond that

Two bar charts comparing who the coordinated network retweets, and who the rest of the network retweets. The coordinated network focuses its retweets around contrarian superspreaders (and some other contrarian users). The rest of the network predominantly retweets conformist (non-contrarian) users, with conformist superspreaders being the most-retweeted overall in this network.

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Alexandros Efstratiou @alextheefstra.eurosky.social · 19/03/2026

Based on common retweets made close in time to each other, we find a coordinated network of accounts whose activity predominantly centers around vaccines/boosters, herd immunity, and excess mortality conversations. These accounts are overall younger than the rest.

A figure showing a coordinated retweet network. The network consists of six sub-clusters, with one being much larger than the rest.

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Alexandros Efstratiou @alextheefstra.eurosky.social · 10/12/2025

More visible accounts in engagement feed are more agitating, less political, get attention from Elon Musk, are not legacy-verified, and are not left-leaning. Other typical effects (e.g., lower exposure for links) also replicated. Right-leaning benefits disappear when controlling for these

A plot showing that accounts with increased visibility in the engagement feed are not legacy-verified, not left-leaning, get more attention from Elon Musk, are more agitating, less political, and post fewer links.

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Alexandros Efstratiou @alextheefstra.eurosky.social · 10/12/2025

Algorithm leads to more political cross-cutting exposure, but also much more centralization. Latter largely driven by outsized increased visibility of platform owner in engagement feed. Right-leaning accounts also enjoy increased visibility; explains increased x-cutting exposure (mostly one-sided)

Plots showing distributions of how centrality differs between engagement and chronological feeds. In the engagement feed, centrality is higher for right-leaning accounts and is much more skewed towards the platform's owner, Elon Musk, compared to the chronological feed.

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Alexandros Efstratiou @alextheefstra.eurosky.social · 23/01/2024

Excited to announce that my paper has just been accepted at The Web Conference (WWW) 2024! I analyze how users willing to engage with opposing views differ in terms of language they use and rewards they receive in their home communities. Preprint coming soon!

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