Five Myths About Influence Operations: What 25 Million Tweets Across Seven State Campaigns Reveal

A set of “stylized facts” about state-backed influence operations now circulates across journalism, policy, and the peer-reviewed literature: that they are monolithic troll armies; that they win by weaponizing moral-emotional language; that they manufacture their own virality; that they learn and optimize against feedback; and that they have become indistinguishable from ordinary users. Most rest on single-campaign studies, uncontrolled comparisons, and large-sample significance reported without baselines or multiple-comparison control, and are rarely re-tested. We assemble complete, government-attributed archives of seven state campaigns (25,076,853 tweets from 9071 accounts) with a matched organic-user baseline for five of them, and re-test all five claims under one protocol: pre-registration, Benjamini–Hochberg false-discovery control, permutation nulls, a future-reception placebo, and a takedown-snapshot decomposition. Scoped to these campaigns, every claim weakens or reverses: the operations are narratively segregated, thinly staffed production desks, not a unified army; an organic moral-contagion law fails to replicate in any of them, and a meaningless placebo predicts engagement as well; internal amplification supplies only 0.10–5.31% of top-percentile reach; the remainder is captured from an external audience whose composition—genuine organic uptake versus coordination the archive cannot see—is structurally unobservable in takedown data, a limit we state as part of the finding; behavior is scripted, with rare apparent feedback mean-reverting toward baseline; and, while their per-account language has drifted off the 2016 “troll” fingerprint, they still coordinate 7–70× more tightly than matched real users—a regularity a frozen re-test reproduces, with the language-drift and segregation patterns, across twelve further country-groups. The five verdicts do not carry equal evidentiary weight: three rest on matched-baseline contrasts, one on a placebo-gated temporal design, and one (the moral-emotional claim) on a placebo-anchored test alone, a hierarchy this paper makes explicit. The corrected picture is coherent: an industrial content factory siloed in production but coordinated in execution, whose reach it does not internally manufacture. The detectable signature has migrated from language to coordination: per-account content fingerprints age out, while cross-account coordination remains the durable, cross-national marker. Because these operations run scripts rather than optimize against feedback, an adversary that genuinely optimized—now feasible with large language models—would look measurably different from the operations studied here: a forward warning, not a present finding. The recurring lesson is methodological: on corpora of confirmed manipulation, baseline-free significance reconstructs the analyst’s expectations, and platform and policy decisions rest on those beliefs.