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Researchers map HPV vaccine discourse reframing on X using multi-layer networks

This paper introduces a new multi-layer network framework designed to detect and analyze the spread of misinformation online. The methodology focuses on identifying low-frequency signals and tracking how discourse is reframed and amplified over time. Applied to 14 years of Italian discourse on X (formerly Twitter) concerning the HPV vaccine, the approach distinguishes between stable, prevention-focused coalitions and emerging skeptical groups. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT Provides a new computational methodology for analyzing online discourse and identifying misinformation.

RANK_REASON This is a research paper published on arXiv detailing a novel computational methodology.

Read on arXiv cs.CL →

COVERAGE [2]

  1. arXiv cs.CL TIER_1 · Lorella Viola ·

    Mapping Discourse Reframing: A Multi-Layer Network Approach to Italian HPV Vaccine Discourse on X (2010-2024)

    arXiv:2605.02629v1 Announce Type: new Abstract: Understanding how online narratives travel through coalitions is critical for identifying information disorder, yet computational analyses often rely on conservative network constructions that erase initially sparse but salient sign…

  2. arXiv cs.CL TIER_1 · Lorella Viola ·

    Mapping Discourse Reframing: A Multi-Layer Network Approach to Italian HPV Vaccine Discourse on X (2010-2024)

    Understanding how online narratives travel through coalitions is critical for identifying information disorder, yet computational analyses often rely on conservative network constructions that erase initially sparse but salient signals. This paper proposes a novel multi-layer fra…