Dynamic Patterns of Personal Networks with Neighbors and Their Determinants After the Great East Japan Earthquake:
Dynamic Patterns of Personal Networks with Neighbors and Their Determinants After the Great East Japan Earthquake:
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东日本大地震后与邻居的个人网络的动态模式及其决定因素：
DOI：
10.11218/ojjams.37.255
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发表时间：
2022
影响因子：
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通讯作者：
Nobuo Suzuki
中科院分区：
文献类型：
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作者：
斉藤知洋;余田翔平・斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;苫米地なつ帆・斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;斉藤知洋;Yuka Minagawa Sugawara;Nobuo Suzuki
自然灾害发生后，邻里网络在受害者和社区的全面恢复中发挥着关键作用。然而，很少有定量研究探讨受害者如何形成，维持，并失去这些网络在灾害发生后很长一段时间。本研究使用东日本大地震受灾者的纵向调查数据，调查了与邻居的人际网络的动态模式及其决定因素。本研究主要从以下三个方面进行分析：（1）对信息和物质交换网络的动态模式的异同进行假设检验;（2）使用灾后约10年的5个调查点的纵向数据;（3）采用基于群体的轨迹建模方法来识别个人网络动态。研究结果表明：（a）同一城市的受害者发展到几种不同的轨迹模式：（B）具体而言，信息交换网络呈现倒U型和低/稳定模式，物质交换网络呈现U型模式，两种网络均呈现下降模式;（c）在这两个网络中，受害者是否发展成更大或更小网络规模的模式取决于他们在灾害发生前的相对优势/劣势差异。
After a natural disaster, neighborhood networks play a key role in the overall recovery of victims and communities. Nevertheless, few quantitative studies have explored how victims form, maintain, and lose these networks over long periods after disasters. In this study, I investigated the dynamic patterns of personal networks with neighbors and their determinants using longitudinal survey data collected from victims of the Great East Japan Earthquake. This analysis focused on three aspects:(1) to test hypotheses regarding similarities and differences in the dynamic patterns of information and material exchange networks;(2) to use longitudinal data from five survey points during approximately 10 years post-disaster; and (3) to adopt a group-based trajectory modeling approach to identify personal network dynamics. The main findings are as follows:(a) Victims in the same city progressed to several different trajectory patterns;(b) Specifically, inverted U-shaped and low/stable patterns were observed for the information exchange network, the U-shaped pattern was a specific trend for the material exchange network, and declining patterns were commonly observed for both networks;(c) In both networks, whether the victims progressed to a pattern of larger or smaller network sizes depended on the relative advantage/disadvantage disparity between them before the disaster.