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The Spontaneous Behavior in Extreme Events: A Clustering-Based Quantitative Analysis

机译:极端事件中的自发行为:基于聚类的定量分析

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Social media records the pulse of social discourse and drives human behaviors in temporal and spatial dimensions, as well as the structural characteristics. These online contexts give us an opportunity to understand social perceptions of people in the context of certain events, and can help us improve disaster relief. Taking Twitter as data source, this paper quantitatively measures exogenous and endogenous social influences on collective behaviors in different events based on standard fluctuation scaling method. Different from existing studies utilizing manual keywords to denote events, we apply a clustering-based event analysis to identify the core event and its related episodes in a hashtag network. The statistical results show that exogenous factors drive the amount of information about an event and the endogenous factors play a major role in the propagation of hashtags.
机译:社交媒体记录了社交话语的脉搏,并在时间和空间尺寸以及结构特征中驱动人类行为。这些在线背景让我们有机会在某些事件的背景下了解对人们的社会看法,并可以帮助我们改善救灾。将Twitter作为数据来源,本文定量测量基于标准波动缩放法的不同事件中集体行为的外源性和内源性社会影响。与利用手册关键字的现有研究不同,我们应用基于集群的事件分析以识别HashTag网络中的核心事件及其相关剧集。统计结果表明,外源性因素驱动了事件的信息量,内源性因素在Hashtags的传播中发挥着重要作用。

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