From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech

TL;DR

This paper explores the theoretical foundations of fear speech across disciplines, reviews datasets, and proposes a taxonomy to advance computational research on fear-based communication.

Contribution

It bridges multiple disciplinary perspectives, reviews existing datasets, and introduces a taxonomy to facilitate future fear speech research.

Findings

Identifies key theoretical perspectives on fear from multiple disciplines

Provides a comprehensive review of existing datasets related to fear speech

Proposes a taxonomy to unify different dimensions of fear in speech

Abstract

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.