Propagation Asymmetry in AI Science Communication: A Three-Speed Structural Model of Technical Myth Formation
Year: 2026
Type: article
Abstract: Recent AI-centered scientific news reports often undergo rapid narrative transformation during downstream dissemination. This study proposes a preliminary structural model—the Three-Speed Translation Model—to analyze such translation dynamics. Narrative transformation is operationalized using three independent indices: Lexical Heat Index (LHI), Subject Substitution Ratio (SSR), and Primary Link Salience (PLS). Using ordered publication layers (Primary Scientific Source → Corporate Communication → Media Coverage → Commentary), we apply Spearman rank analysis to examine directional translation patterns. Preliminary results suggest asymmetric dynamics: LHI increases across downstream layers, SSR peaks at the corporate layer before stabilizing, and PLS decreases progressively. Mythologization is operationally defined as a measurable increase in lexical thermalization combined with decreased primary-source salience across ordered publication layers. This pilot study establishes a structural and measurable framework for analyzing technological myth formation and invites further cross-domain validation.
Author: Kimura, Hinano
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7130857922
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