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用于模仿人类语言交流，并在各类社交网络服务(SNS)中生成有毒或煽动性内容。机器人传播的虚假信息可能通过复杂交织的因素——如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、国家认同感的认知偏移、错误社会规范的传播以及集体记忆的长期操纵——以隐蔽而深刻的方式重塑社会进程。然而，从孤立的SNS分析中推断机器人在混合化、多语言及异质性媒体生态中的多能性仍属未知领域，这凸显了亟需构建全面框架以刻画机器人对公民话语的涌现风险。本文提出一种跨学科框架来表征机器人的多能性，整合了影响力量化、网络动态监测及跨语言特征分析。将该框架应用于俄乌冲突相关的地缘政治话语分析时，跨语言毒性画像与网络分析的结果揭示了亲俄与亲乌人类及机器人在混合SNS中的时空轨迹。在社交媒体战争中，武器化机器人主要栖身于X平台，而人类主要活跃于Reddit平台。这一严格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、回音室形成及集体记忆表现等机制背后的人机协同机制。