Burstier Events: Analysing Human Memory Over a Century of Events Using The New York Times

Over the last few decades, psychologists have increasingly found that the mind stores and uses the statistics of its environment. However, less work has analyzed whether the environmental statistics have changed and what that would imply for the mind. In this chapter, we consider human memory as the solution to the computational problem of predicting what events will happen next given a history of past events. Prior work examining two years of data (1986-1987) found that the environmental statistics of events occurring in the world are reflected in human memory of events, such as practice and retention effects. We analyse the last century of event statistics by assuming that words in the headlines The New York Times are each an event. While presenting our methods, we do so in the form of a case study – we discuss general practices for behavioural data science projects, standard issues that arise, and how to resolve different issues as they arise for the presented analyses. After replicating prior work analysing event statistics in this manner during 1986-1987, we extend the methodology to the last century (1919-2019). Our analyses suggest that the events are occurring in denser bursts, meaning that when a new event occurs in the last few years, this event reoccurs more often in the short-term and less often in the long-term (as compared to events that first occur in the early 20th century). This suggests that human memory faces different environmental demands than it has in the past and may be adapting to the dynamics of event statistics. Keywords: behavioural data science, rational analysis, human memory