The abstract begins: “We understand the dynamics of the world around us
as by associating pairs of events, where one event has some influence on the
other. These pairs of events can be aggregated into a web of memories
representing our understanding of an episode of history. The events and the
associations between them need not be directly experienced—they can also be
acquired by communication. In this paper we take a network approach to study
the dynamics of memories of history. First we investigate the network structure
of a data set consisting of reported events by several individuals and how
associations connect them. We focus our measurement on degree distributions,
degree correlations, cycles (which represent inconsistencies as they would break
the time ordering) and community structure. We proceed to model effects of
communication using an agent-based model. We investigate the conditions for the
memory webs of different individuals to converge to collective memories, how
groups where the individuals have similar memories (but different from other
groups) can form. Our work outlines how the cognitive representation of
memories and social structure can co-evolve as a contagious process. We
generate some testable hypotheses including that the number of groups is
limited as a function of the total population size."
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