Anthropomorphic social bots are engineered to emulate human verbal communication and generate toxic or inflammatory content across social networking services (SNSs). Bot-disseminated misinformation could subtly yet profoundly reshape societal processes by complexly interweaving factors like repeated disinformation exposure, amplified political polarization, compromised indicators of democratic health, shifted perceptions of national identity, propagation of false social norms, and manipulation of collective memory over time. However, extrapolating bots' pluripotency across hybridized, multilingual, and heterogeneous media ecologies from isolated SNS analyses remains largely unknown, underscoring the need for a comprehensive framework to characterise bots' emergent risks to civic discourse. Here we propose an interdisciplinary framework to characterise bots' pluripotency, incorporating quantification of influence, network dynamics monitoring, and interlingual feature analysis. When applied to the geopolitical discourse around the Russo-Ukrainian conflict, results from interlanguage toxicity profiling and network analysis elucidated spatiotemporal trajectories of pro-Russian and pro-Ukrainian human and bots across hybrid SNSs. Weaponized bots predominantly inhabited X, while human primarily populated Reddit in the social media warfare. This rigorous framework promises to elucidate interlingual homogeneity and heterogeneity in bots' pluripotent behaviours, revealing synergistic human-bot mechanisms underlying regimes of information manipulation, echo chamber formation, and collective memory manifestation in algorithmically structured societies.

翻译：拟人化社交机器人被设计为模仿人类言语交流，并在社交网络服务中生成有害或煽动性内容。机器人传播的错误信息可能通过重复性虚假信息暴露、加剧的政治两极分化、民主健康指标的受损、民族认同感知的偏移、虚假社会规范的传播以及集体记忆的长期操纵等复杂交织因素，潜移默化却又深刻地重塑社会进程。然而，从孤立的社交网络服务分析中推断机器人在混合化、多语言和异质性媒体生态中的多能性仍属未知，这凸显了建立全面框架以表征机器人对公民话语的突发风险的必要性。本文提出一个跨学科框架来表征机器人的多能性，融合了影响力量化、网络动态监测和跨语言特征分析。当将该框架应用于俄乌冲突地缘政治话语时，跨语言毒性分析和网络分析的结果阐明了亲俄与亲乌人类及机器人在混合社交网络服务中的时空轨迹。在社交媒体战争中，武器化机器人主要存在于X平台，而人类用户则主要活跃于Reddit。这一严谨的框架有望阐明机器人多能行为中的跨语言同质性与异质性，揭示算法化社会中信息操纵、回音室形成和集体记忆呈现背后的人类-机器人协同机制。