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

TL;DR
This paper introduces a multi-layer network framework to analyze the evolution of HPV vaccine discourse on X over 14 years, capturing emerging signals of information disorder and polarization.
Contribution
It presents a novel dual-layer approach combining conservative community detection with fringe hashtag projection to better identify problematic discourse signals.
Findings
Revealed stable prevention coalitions contrasted with separable skepticism groups.
Improved detection of long-tail problematic hashtags with the coverage layer.
Characterized the structural maturation of polarized narratives over time.
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 signals. This paper proposes a novel multi-layer framework that captures low-frequency signals of emerging information disorder allowing for locating where online discourse is reframed and amplified over time. The use case is 14 years of Italian discourse on X regarding the Human Papillomavirus (HPV) vaccine across three pivotal epochs (2010-2024). Utilizing hashtag co-occurrence networks, we introduce a dual-layer approach. We first identify robust core discourse coalitions through conservative community detection, revealing a stable prevention-oriented backbone contrasted with increasingly separable skepticism coalitions. We then introduce a coverage layer and…
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