叙事分歧和错误信息:评估公共信息来源信息实用性的输入模型
José Ignacio Peláez1,2,3, Gustavo Fabian Vaccaro1,3, Felix Infante León1,3
1Center for Applied Social Research (CISA), University of Málaga, 29010 Málaga, Spain.
Entropy (Basel, Switzerland)
|February 27, 2026
概括
错误信息会造成叙述的混乱和认识的不一致. 一个新的计算模型量化了这种叙事分歧,提供了一个分析和打击信息系统中错误信息动态的工具.
科学领域:
- 计算社会科学 计算社会科学
- 信息科学 信息科学 信息科学
- 沟通研究 沟通研究
背景情况:
- 虚假信息侵蚀了公民的自治和公共话语的稳定性.
- 它表现为叙事分歧,导致碎片化和结构连贯性丧失.
- 现有的方法往往侧重于事实检查,忽视叙事结构.
研究的目的:
- 通过的结构框架来检查虚假信息,将其定义为叙事障碍.
- 开发一个计算模型来量化叙事分歧和认识体系不一致.
- 评估叙事连贯性和信息实用性作为认识价值的指标.
主要方法:
- 开发了QVP-RI (关系信息估值) 运算符,一个计算模型.
- 利用最先进的自然语言处理 (NLP) 管道和分析.
- 使用信息和规范化结构分歧的量化叙事分歧.
主要成果:
- 结构-型模型在500名参与者中经过实验验证.
- 确定了高度分歧的区域,揭示了通信漏洞.
- 展示了叙事障碍如何促进虚假信息的动态.
结论:
- QVP-RI 运营商提供了一个基于计算的工具,用于分析虚假信息.
- 它提供了一种方法来加强开放信息系统中的认识体系秩序.
- 该方法超越了简单的准确性评估,以评估信息的有用性.
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