梳理恐惧话语的理论基础，构建系统分类框架。
From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech
- 跨学科对比心理学、政治学等领域的恐惧理论
- 整合现有数据集并提出恐惧话语多维分类体系
- 为平台治理与研究提供可落地的理论工具
恐惧具有动员社会、扭曲沟通和重塑集体行为的强大影响力。在计算语言学中，恐惧主要被当作情绪研究，而非一种独立的话语形式。恐惧话语内容广泛且持续增长，常比仇恨言论具有更高的传播范围和互动性，因其表现更‘文明’而易规避审核。然而，恐惧话语的计算研究仍分散且资源匮乏。这源于恐惧话语本身是多学科共同塑造的现象。本文通过对比心理学、政治学、传播学和语言学中的恐惧理论，梳理现有定义，回顾相关领域数据集，并提出一个整合恐惧多维度特征的分类体系。通过审查现有数据集并明确核心概念，本工作为构建新数据集及推进恐惧话语研究提供了理论与实践指引。
原文摘要 · Abstract (English)
Few forces rival fear in their ability to mobilize societies, distort communication, and reshape collective behavior. In computational linguistics, fear is primarily studied as an emotion, but not as a distinct form of speech. Fear speech content is widespread and growing, and often outperforms hate-speech content in reach and engagement because it appears "civiler" and evades moderation. Yet the computational study of fear speech remains fragmented and under-resourced. This can be understood by recognizing that fear speech is a phenomenon shaped by contributions from multiple disciplines. In this paper, we bridge cross-disciplinary perspectives by comparing theories of fear from Psychology, Political science, Communication science, and Linguistics. Building on this, we review existing definitions. We follow up with a survey of datasets from related research areas and propose a taxonomy that consolidates different dimensions of fear for studying fear speech. By reviewing current datasets and defining core concepts, our work offers both theoretical and practical guidance for creating datasets and advancing fear speech research.
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