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The Mechanism of Crowd Stampede Based on Case Statistics through SNA Method

机译:基于SNA方法的案例统计的人群踩踏机制

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Stampede is a concern of urban pubic security management. The current academic research focus is the identification of risk factors of trampling accidents and determination of correlation patterns and accident-causing mechanisms among stampede elements in order to effectively obtain the influencing factors of stampede and clarify the transmission routes of stampede risk factors. Previous index cases were scrutinized and analyzed in 78 typical stampedes from 2010 - 2019 based on "pedestrian-equipment-environment-management" framework, and 17 influencing factors of stampede by adopting a conceptual coding method were obscured. Then, the degree centrality, intermediate centrality and respective weights of the influencing factors were calculated based on the social network analysis (SNA) method. The influencing level of the factors was signified, and the transmission mechanism of risk in the system network was determined. The results reveal that the degree centrality and weight with conspicuous features of over-density of crowds, pedestrian swarming and falling, and insufficient on-site transactions contribute the most. This finding indicates that these factors play a relatively major role in the stampede system. Furthermore, the intermediate centrality of insufficient on-site transactions is the top factor, meaning that this factor has a strong controlling force in the incident system and considerably influences other factors. This study shows that the SNA method is feasible in analyzing the mechanism of stampede incidents, simultaneously addressing the shortcomings of the linear statistical model of factors and providing theoretical support for comprehensive control of crowd risk.
机译:Stampede是城市寄宿安全管理的关注。目前的学术研究重点是识别践踏事故的危险因素和踩踏元素之间的相关模式和事故导致机制的危险因素,以便有效地获得踩踏的影响因素,并澄清踩踏风险因素的传输路线。以前的索引案例在2010年至2019年的78个典型的冲压件上分析,基于“行人 - 设备 - 环境管理”框架,通过采用概念编码方法,17个影响因素的踩踏因素被遮挡。然后,基于社交网络分析(SNA)方法计算了影响因子的程度中心,中间中心和各自的重量。意味着因素的影响程度,并确定了系统网络风险的传输机制。结果表明,度数和重量与人群过度密度的显着特征,行人蜂拥而至,现场交易不足的贡献最多。这一发现表明这些因素在踩踏系统中发挥了相对重要的作用。此外,现场交易不足的中间中心是最高因素,这意味着该因素在事故系统中具有强大的控制力,并且大大影响了其他因素。本研究表明,SNA方法在分析踩踏事件的机制方面是可行的,同时解决因素线性统计模型的缺点,并为人群风险综合控制提供理论支持。

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