粗糙、商业与自我指涉：日语X平台上的中文协同行为
Crude, Commercial, and Self-Referential: Chinese-Language Coordinated Activity in Japanese-Language X
AI总结：
本研究利用超73万中文协同账户及4.95亿帖文数据，刻画了日语X平台上粗糙中文协同行为的特征、内容性质及用户反应，发现其多具自动化痕迹、内容非政治化且传播主要依赖自我指涉。
AI中文摘要：
恶意协同行为长期以来被视为信息生态系统污染的主要来源。本文聚焦于基于文本重复的粗糙协同行为。随着缓解其传播的需求增长，学者们对此类协同行为进行了研究，尤其关注机器人检测。然而，很少有研究对恶意协同行为本身进行刻画，或考察其如何引发普通用户的反应。利用2024年5月至2026年3月间发布的734,173个中文协同账户及约4.95亿条协同帖文的数据集，本研究分析了协同行为的特征以及普通用户对协同帖文的反应。我们报告三项发现：（1）大多数协同账户是粗糙的，保留了经典的自动化痕迹，而对同月日语账户应用相同标准所得比例低六倍；（2）其内容绝大多数是非政治性的；（3）就其传播范围而言，在大型可观测级联中，多数反应来自协同账户自身，而被归类为潜在有害或非法材料的帖文则获得来自非中文主导人群的较高比例反应。我们提供了出现在X日语分类流中的粗糙中文协同行为的时间纵向定量图谱。
英文摘要：
Malicious coordination has long been regarded as a principal source of information ecosystem pollution. Here, we focus on crude, text-repetition-based coordination. As the demand for mitigating its dissemination has grown, scholars have studied such coordination, focusing especially on bot detection. Few studies, however, have characterized malicious coordination per se or examined how it elicits reactions from general users. Leveraging a dataset of 734,173 Chinese-language coordinated accounts and around 495 million coordinated posts published between May 2024 and March 2026, this study analyzes the characteristics of coordinated behavior and how general users react to coordinated posts. We report three findings: (1) most coordinated accounts are crude and retain the classic marks of automation, and the same criterion applied to Japanese-language accounts over the same month yields a share six times lower; (2) their content is overwhelmingly non-political; (3) regarding their reach, most reactions within large observable cascades originate from coordinated accounts themselves, while posts classified as potentially harmful or illegal material receive a comparatively high proportion of reactions from outside the Chinese-dominant population. We provide a longitudinal quantitative map of crude Chinese-language coordination appearing in X's Japanese-classified stream.
