提出了一种基于模糊逻辑和特征驱动分析的暗示性影响检测与分类方法

Yuliia Nakonechna
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引用次数: 0

摘要

本研究提出了一种方法来识别和分类信息操作中使用的旨在发挥暗示性影响的工具。该方法将模糊集理论和模糊推理方法与基于特征的分析方法相结合。通过采用这种方法,研究的重点是识别和分类工具,如宣传、虚假、虚假信息、操纵和人为叙述。该框架提供了对信息行动中采用的各种战术的全面和细致的理解,从而改进了分析和缓解战略。
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Proposing of suggestive influence detection and classification method based on fuzzy logic and feature driven analysis
This research proposes an approach to identify and classify tools utilized in information operations that aim to exert suggestive influence. The proposed method combines fuzzy sets theory and fuzzy inference methods with a feature-based analysis approach. By employing this approach, the study focuses on identifying and categorizing tools such propaganda, fake, disinformation, manipulation, and artificial narrative. This framework provides a comprehensive and nuanced understanding of the various tactics employed in information operations, allowing for improved analysis and mitigation strategies.
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