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Public memories of significant events shared within societies and groups havebeen conceptualized and studied as collective memory since the 1920s. Thanks tothe recent advancement in digitization of public-domain knowledge and onlineuser behaviors, collective memory has now become a subject of rigorousquantitative investigation using large-scale empirical data. Earlier studies,however, typically considered only one dynamical process applied to dataobtained in just one specific event category. Here we propose a two-phasemathematical model of collective memory decay that combines exponential andpower-law phases, which represent fast (linear) and slow (nonlinear) decaydynamics, respectively. We applied the proposed model to the Wikipedia pageview data for articles on significant events in five categories: earthquakes,deaths of notable persons, aviation accidents, mass murder incidents, andterrorist attacks. Results showed that the proposed two-phase model comparedfavorably with other existing models of collective memory decay in most of theevent categories. The estimated model parameters were found to be similaracross all the event categories. The proposed model also allowed for detectionof a dynamical switching point when the dominant decay dynamics exhibit a phaseshift from exponential to power-law. Such decay phase shifts typically occurredabout 10 to 11 days after the peak in all of the five event categories.

A two-phase model of collective memory decay with a dynamical switching point