Online social network has become a new form of infrastructure for communities in spreading situational information in disasters. Developing effective interventions to improve the network performance of information diffusion is essential for people to rapidly retrieve information in coping with disasters and subsequent disruptions. Existing studies have investigated multiple aspects of online social networks in stationary situations and a separate manner. However, the networks are dynamic and different properties of the networks are co-related in the evolving disaster situations. In particular, disaster events motivate people to communicate online, create and reinforce their connections, and lead to a dynamic reticulation of the online social networks. To understand the relationship among these elements, we proposed an Online Network Reticulation (ONR) framework to examine four modalities (i.e., enactment, activation, reticulation, and network performance) in the evolution of online social networks to analyze the interplays among disruptive events in disasters, user activities, and information diffusion performance on social media. Accordingly, we examine the temporal changes in four elements for characterization of reticulation: activity timing, activity types (post, share, reply), reticulation mechanism (creation of new links versus reinforcement of existing links), and structure of communication instances (self-loop, converging, and reciprocal). Finally, the aggregated effects of network reticulation, using attributed network-embedding approach, are examined in the average latent distance among users as a measure of network performance for information propagation. The application of the proposed framework is demonstrated in a study of network reticulation on Twitter for a built environment disruption event during 2017 Hurricane Harvey in Houston. The results show that the main underlying mechanism of network reticulation in evolving situations was the creation of new links by regular users. The main structure for communication instances was converging, indicating communication instances driven by information-seeking behaviors in the wake of a disruptive event. With the evolution of the network, the proportion of converging structures to self-loop and reciprocal structures did not change significantly, indicating the existence of a scale-invariance property for network structures. The findings demonstrate the capability of the proposed online network reticulation framework for characterizing the complex relationships between events, activities, and network performance in online social networks during disasters.

中文翻译：

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表征灾难期间在线社交网络中的网状结构

在线社交网络已成为社区在灾难中传播情况信息的一种新的基础设施形式。制定有效的干预措施来改善信息传播的网络性能，对于人们快速应对灾难和后续破坏的信息至关重要。现有研究已经在固定情况下以单独的方式研究了在线社交网络的多个方面。但是，网络是动态的，并且在不断演变的灾难情况下，网络的不同属性是相互关联的。特别是，灾难事件激发人们在线交流，建立和加强他们的联系，并导致在线社交网络的动态网状化。要了解这些元素之间的关系，我们提出了一个在线网络网状结构（ONR）框架，以检查在线社交网络发展过程中的四种模式（即制定，激活，网状化和网络性能），以分析灾难，用户活动和信息传播中的破坏性事件之间的相互作用。在社交媒体上的表现。因此，我们研究了表征网状结构的四个要素的时间变化：活动时间，活动类型（发布，共享，回复），网状结构机制（新链接的创建与现有链接的增强）以及通信实例的结构（自我-循环，收敛和倒数）。最后，使用归因网络嵌入方法，网络网状结构的聚合效应，对用户之间的平均潜在距离进行了检查，以衡量信息传播的网络性能。在针对2017年休斯敦哈维飓风期间的建筑环境破坏事件在Twitter上进行的网状网络研究中，证明了所建议框架的应用。结果表明，在不断变化的情况下，网络网状结构的主要底层机制是普通用户创建新链接。通信实例的主要结构是会聚的，指示发生破坏性事件后，由信息寻求行为驱动的通信实例。随着网络的发展，会聚结构与自环和互易结构的比例没有显着变化，这表明网络结构存在尺度不变性。