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Narrative Divergence and Disinformation: An Entropic Model for Assessing the Informative Utility of Public

José Ignacio Peláez1,2,3, Gustavo Fabian Vaccaro1,3, Felix Infante León1,3

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Entropy (Basel, Switzerland)
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Summary

Disinformation creates narrative disorder and epistemic incoherence. A new computational model quantifies this narrative divergence, offering a tool to analyze and combat disinformation dynamics in information systems.

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disinformation modelingepistemic coherenceinformational entropyinformative utilitynarrative divergencenatural language processing (NLP)semantic distance

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Area of Science:

  • Computational Social Science
  • Information Science
  • Communication Studies

Background:

  • Disinformation erodes civic autonomy and public discourse stability.
  • It manifests as narrative divergence, causing fragmentation and loss of structural coherence.
  • Existing approaches often focus on fact-checking, neglecting narrative structure.

Purpose of the Study:

  • To examine disinformation through an entropic structural framework, defining it as narrative disorder.
  • To develop a computational model for quantifying narrative divergence and epistemic incoherence.
  • To evaluate narrative coherence and informational utility as indicators of epistemic value.

Main Methods:

  • Developed the QVP-RI (Relational Information Valuation) operator, a computational model.
  • Utilized state-of-the-art Natural Language Processing (NLP) pipelines and entropic analysis.
  • Quantified narrative divergence using informational entropy and normalized structural divergence.

Main Results:

  • The structural-entropic model was experimentally validated with 500 participants.
  • Identified high divergence regions, revealing communication vulnerabilities.
  • Demonstrated how narrative disorder facilitates disinformation dynamics.

Conclusions:

  • The QVP-RI operator offers a computationally grounded tool for analyzing disinformation.
  • It provides a method to strengthen epistemic order in open information systems.
  • The approach moves beyond simple accuracy assessments to evaluate informational utility.