Community formation in socio-spatial human networks is one of the important mechanisms for mitigating hazard impacts of extreme weather events. Research is scarce regarding latent network characteristics shaping community formation in human mobility networks during natural disasters. Here, we examined human mobility networks in Harris County, Texas, in the context of the managed power outage forced by 2021 Winter Storm Uri to detect communities and to evaluate latent characteristics in those communities. We examined three characteristics in the communities formed within human mobility networks: hazard-exposure heterophily, socio-demographic homophily, and social-connectedness strength. The results show that population movements were shaped by socio-demographic homophily, heterophilic hazard exposure, and social connectedness strength. Our results also indicate that a community encompassing more high-impact areas would motivate population movements to areas with weaker social connectedness. Our findings reveal important characteristics shaping community formation in human mobility networks in hazard response. Specific to managed power outages, formed communities are spatially co-located, underscoring a best management practice to avoid prolonged power outages among areas within communities, thus improving hazard exposure heterophily. The findings have implications for power utility operators to account for the characteristics of socio-spatial human networks when determining the patterns of managed power outages.

翻译：社会空间人类网络中的社区形成是减轻极端天气事件灾害影响的重要机制之一。目前关于自然灾害期间人类移动网络中塑造社区形成的潜在网络特征研究尚显不足。本研究以2021年冬季风暴乌里引发的计划停电事件为背景，通过分析德克萨斯州哈里斯县的人类移动网络，检测社区形成并评估其潜在特征。我们重点考察了人类移动网络内形成社区的三个特征：灾害暴露异质性、社会人口同质性和社会连接强度。结果表明，人口流动受到社会人口同质性、异质性灾害暴露和社会连接强度的共同影响。研究还发现，包含更多高影响区域的社区会促使人口向社会连接较弱的区域流动。本研究揭示了灾害响应过程中人类移动网络社区形成的重要特征。针对计划停电情景，形成的社区在空间上呈现共位分布，这提示最佳管理实践应避免社区内部区域出现长时间停电，从而改善灾害暴露异质性。这些发现对电力运营商在制定计划停电方案时考虑社会空间人类网络特征具有重要参考价值。