There he is, says I, in his gloryhole, with his cruiskeen lawn and his load of papers, working for the cause
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.
When we think and talk about changes in the world around us, we weave together discrete episodes to create a narrative. Events along the timeline of this narrative are connected by associations. For instance, if we recall that “since the gas price went up, I decided to buy a fuel-efficient car”, we can represent “gas price going up” and “I buying a fuel-efficient car” as two nodes of a directed graph with an associative arc connecting the former to the latter. Such arcs need not be a first-hand experience; we might believe that “increased political tension in the middle-East drove the gas price up” drawing an arc from “increased political tension in the middle-East” to “gas price going up”. Our recollection and understanding of the past can thus be represented as a web of events connected by associations like the above example.
Such autobiographical narratives take place within a social context. They are fluid and dynamic, bearing the hallmark of the social context within which they emerge. Associations between events are not only dependent on the personal experiences of the individual, but also on social processes of construction and re-construction that ultimately give place to what we experience as a collective history. Much of the social processes of collective history occur in conversational and communicative contexts, which convey personal and social meaning to events. Communication reinforces the memories of interacting individuals, and it is through this process that associative arcs can spread in a population so that memory webs come to share common elements across people. From this process, associative arcs can spread in a population so that groups of people share part of their webs of memories. We call such subnetworks in common to many people collective memories.
In this paper, we will investigate a model of how the web of memories of a population evolves, including the mechanisms mentioned above. We use the model to investigate the stability of collective memories, the minimal requirements for cycles (sequences of associations that must violate the time-ordering of the events) and the possibility that communication can lead to the formation of groups sharing collective memories. There are other conceivable mechanisms than communication for the evolution of a person’s web of memories: first-hand experiences, mass-medial information and logical deduction (to fill out gaps in one’s web of memories). In our model of the dynamics of collective memories these other mechanisms are grouped together and, as opposed to communication, treated as external input to the model.
Communications as a process for the understanding of history—the formation of causal networks, both on an individual and aggregate level—has been studied in the qualitative tradition of social and behavioral sciences. One has investigated the processes behind collective memories—how groups of people maintain a common narrative of a period of history. This type of research are to a large extent case studies about, ethnic groups’ memories of traumatic events, like the Jews’ collective memories of the holocaust, or comparative studies like the Palestinians and Israelis different histories of the state of Israel.
Recently there has been a considerable interest in models of the spreading of information and opinions between people. Such studies have for example investigated the minimal requirements for fads to spread, for groups of people to make correct collective decisions or predictions, and the conditions for a diversity of opinions (as opposed to a widespread consensus) to be the result of communication. In the present work we follow this tradition and create a model of collective memory emerging from communication. This model will take a web of memories as input. In this study we take this input network from an empirical dataset. The paper starts discussing the structure of this empirical data, then proceeds to the construction of the model and finally discusses the results of the simulations.
collage { Lola Dupré }
