具有动态切换点的集体记忆衰减的两相模型
A two-phase model of collective memory decay with a dynamical switching point
摘要：
自20世纪20年代以来，社会和群体内部共享的重大事件的公共记忆被概念化并作为集体记忆进行研究。由于公共领域知识和在线用户行为数字化的最新进展，集体记忆现在已经成为使用大规模经验数据进行严格定量研究的主题。然而，早期的研究通常只考虑一个动态过程，应用于在一个特定的事件类别中获得的数据。在这里，我们提出了一个两阶段的集体记忆衰减的数学模型，结合指数和幂律阶段，分别代表快速（线性）和缓慢（非线性）的衰减动力学。我们将所提出的模型应用于维基百科的页面浏览数据，这些页面浏览数据涉及五类重大事件：地震、名人死亡、航空事故、大规模谋杀事件和恐怖袭击。结果表明，提出的两阶段模型与其他现有的集体记忆衰退模型相比，在大多数的事件类别。发现所有事件类别的估计模型参数相似。该模型还允许检测的动态切换点时，占主导地位的衰减动态表现出从指数到幂律的相移。这种衰变相移通常发生在所有五种事件类别的峰值之后约10至11天。
英文摘要：
Public memories of significant events shared within societies and groups have been conceptualized and studied as collective memory since the 1920s. Thanks to the recent advancement in digitization of public-domain knowledge and online user behaviors, collective memory has now become a subject of rigorous quantitative investigation using large-scale empirical data. Earlier studies, however, typically considered only one dynamical process applied to data obtained in just one specific event category. Here we propose a two-phase mathematical model of collective memory decay that combines exponential and power-law phases, which represent fast (linear) and slow (nonlinear) decay dynamics, respectively. We applied the proposed model to the Wikipedia page view data for articles on significant events in five categories: earthquakes, deaths of notable persons, aviation accidents, mass murder incidents, and terrorist attacks. Results showed that the proposed two-phase model compared favorably with other existing models of collective memory decay in most of the event categories. The estimated model parameters were found to be similar across all the event categories. The proposed model also allowed for detection of a dynamical switching point when the dominant decay dynamics exhibit a phase shift from exponential to power-law. Such decay phase shifts typically occurred about 10 to 11 days after the peak in all of the five event categories.
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