The power of Alternative Influence Networks (AIN) for spreading Covid-19 problematic information on Facebook during a year of pandemic

Summary

This paper investigates how Alternative Influence Networks (AINs) propagated Covid-19 problematic information on Italian Facebook during the pandemic’s first year (March 2020 – March 2021). Drawing on a corpus of 175,228 posts from previously identified covid-skeptic accounts engaged in coordinated link sharing, the authors combine k-means clustering of mentioned public figures with engagement analysis and deductive content analysis to map the actors driving covid-skeptic discourse. They argue that an Italian “Intellectual Dark Web” (IDW) cluster — composed of intellectuals, academics, and dissident celebrities — functions as a particularly potent amplification engine, but that the broader circulation of conspiracy and no-vax narratives still hinges on legacy media: covid-skeptic claims travel largely as remediated quotations from TV talk shows and newspaper interviews, a manipulation strategy that is structurally resistant to fact-checking.

Key Contributions

• Empirically maps the Italian AIN active during Covid-19 and isolates an “Intellectual Dark Web” sub-cluster distinct from politicians, journalists, and experts.
• Operationalizes a comments/shares ratio metric (adapted from prior coordinated-behavior work) to distinguish amplification-oriented from debate-oriented engagement.
• Extends Bolter and Grusin’s remediation concept to show how alternative media weaponize legacy-media-sourced expert statements, complicating fact-checking.
• Provides Italian empirical evidence for the hybrid-media-system, AIN, and infodemic literatures.

Methods

• Collected 175,228 Facebook posts via CrowdTangle from a pre-identified list of Italian covid-skeptic accounts flagged through coordinated link-sharing analysis.
• Extracted capitalized strings across message, title, description, and image-text fields; manually classified the top 2,000 proper nouns into five (non-mutually-exclusive) categories, yielding 254 names, reduced to 79 after removing institutional/apical roles.
• Applied k-means clustering, yielding five clusters of mentioned figures.
• Identified 21,390 posts mentioning these figures; computed engagement descriptive statistics and a comments/shares ratio (range −1 to 1).
• Conducted deductive content analysis on a stratified sample of 150 top-engaging posts (10 per cluster × 3 comments/shares strata).

Findings

• Five clusters emerged: Politicians, Other Public Figures, Journalists, Doctors/Scientists/Experts, and IDW Influencers.
• IDW Influencers had the lowest comments/shares ratio (−0.28), signaling share-heavy hyperpartisan amplification; Doctors/Scientists/Experts also skewed share-heavy (−0.21).
• Journalists drew the most contested engagement (ratio 0.16, comment-heavy).
• Politicians produced the largest volume of posts (9,879) but lower mean engagement; IDW Influencers and Other Public Figures posted least but garnered the highest average and median interactions.
• The top 10% most-engaging posts were dominated by journalist figures (Nicola Porro, Gianluigi Paragone) and legacy outlets (La Verità, Libero), with AIN micro-celebrities ranking just behind.
• Content analysis showed that covid-skeptic, no-vax, and conspiracy claims most often circulated as remediated quotations from mainstream TV and print, not as original alternative-media content.

Connections

This work builds directly on the Italian coordinated link-sharing tradition that produced the underlying account list, connecting closely to Giglietto2023-fa71a001 and Giglietto2026-9b6a992d. Its focus on pandemic-era problematic health information and influencer-driven amplification dialogues with Pante2025-pq and Kansaon2025-id, while its argument about legacy-media remediation as a vector for misinformation resonates with broader work on hybrid-media amplification dynamics such as Hurcombe2025-cs.