发表机构
Information Sciences Institute, University of Southern California; University of Maryland（南加州大学信息科学研究所; 马里兰大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用2024年大选期间286万条社交媒体帖子，统一建模六种群体间敌意理论，发现边界建构与威胁建构为核心，机制按规律顺序出现，为计算社会科学提供实证基础。
AI 中文摘要
针对社会群体的敌意言论可以使排斥行为正常化，并为虐待行为辩护，同时加剧日益严重的两极化和政治暴力。缓和在线言论中敌意言论的努力借鉴了社会心理学、道德心理学和政治学的基础理论。然而，这些理论在很大程度上是并行发展的，常常提出关于敌意如何发展的不同甚至相互矛盾的论述，并且很少在真实话语中相互检验。其结果是，对敌意的修辞机制的理解支离破碎，缺乏对其在现实世界话语中如何出现及相互关联的清晰认识。利用2024年美国总统大选期间来自TikTok、Truth Social和Twitter/X的286万条帖子，我们在一个共同的实证框架内，对六种群体间敌意基础理论——边界建构、威胁建构、替罪羊化、负面评价、去人性化和行动导向——的机制进行建模，以恢复群体间敌意修辞的更广泛组织。在结构上，我们发现边界建构和威胁建构锚定了该系统；在时间上，我们发现这些机制往往遵循一种规律性的顺序：边界建构、贬损和行动导向往往较早出现；去人性化和威胁建构较晚出现；替罪羊化最晚出现。绘制这些理论框架在话语中的实际表现，弥合了社会科学传统之间的长期分歧，并为计算社会科学提供了更清晰的实证基础，以建模超越单一标签检测的群体间敌意修辞。
英文摘要
Hostile rhetoric toward social groups can normalize exclusion and justify mistreatment, as well as contribute to rising polarization and political violence. Efforts to moderate hostile rhetoric in online speech draw on foundational theories in social and moral psychology, and political science. However, these theories were developed largely in parallel, often propose different and sometimes conflicting accounts of how hostility develops, and have rarely been tested against each other in real discourse. The result is a fragmented understanding of the rhetorical mechanisms of hostility, without a clear sense of how they appear, and relate to each other, in real-world discourse. Using 2.86 million posts from TikTok, Truth Social, and Twitter/X during the 2024 U.S. presidential election, we model the mechanisms of six foundational theories of intergroup hostility -- boundary construction, threat construction, scapegoating, negative evaluation, dehumanization, and action orientation -- within a common empirical framework to recover the broader organization of intergroup hostility rhetoric. Structurally, we find that boundary construction and threat construction anchor the system; temporally, we find that these mechanisms tend to follow a regular ordering: boundary construction, derogation, and action orientation tend to appear early; dehumanization and threat construction later; scapegoating latest. Mapping how these theoretical frameworks actually manifest in discourse bridges longstanding divisions across social science traditions and presents computational social science with a clearer empirical foundation for modeling intergroup hostility rhetoric beyond single-label detection.
Comments16 pages
