Computational behavior theory and cultural evolution
As announced a few weeks ago, our paper “The Logic of Fashion Cycles” has been published, and is freely available on the PLoS ONE website. You can find a good summary at The National Post.
Plos ONE has accepted our paper “The logic of fashion cycles,” where Alberto Acerbi, Magnus Enquist and myself present a new theoretical model to understand fashion cycles (see my previous post on dog breeds). You can download a preprint, and here is the abstract:
Many cultural traits exhibit volatile dynamics, commonly dubbed fashions or fads. Here we show that realistic fashion-like dynamics emerge spontaneously if individuals can copy others’ preferences for cultural traits as well as traits themselves. We demonstrate this dynamics in simple mathematical models of the diffusion, and subsequent abandonment, of a single cultural trait which individuals may or may not prefer. We then simulate the coevolution between many cultural traits and the associated preferences, reproducing power-law frequency distributions of cultural traits (most traits are adopted by few individuals for a short time, and very few by many for a long time), as well as correlations between the rate of increase and the rate of decrease of traits (traits that increase rapidly in popularity are also abandoned quickly and vice-versa). We also establish that alternative theories, that fashions result from individuals signaling their social status, or from individuals randomly copying each other, do not satisfactorily reproduce these empirical observations.
I have recently attended a one-day course on data visualization with Edward Tufte and I have tried to put his advice on virtual paper in this supergraphic on the popularity of dog breeds, using AKC data (courtesy of Hal Herzog). The graph shows the popularity of 100 breeds over time (most popular breeds first), indicating the maximum in popularity and other peaks (if any). I have produced this graph as an inspiration for my ongoing work on cultural dynamics (some features are idiosyncratic to the data analyses I am making). Here are a few things I see in the graph:
What else can you see? And how to explain it? In am working, with Alberto Acerbi and Magnus Enquist on an explanation of fashion cycles based on the cultural dynamics of preferences, as foreshadowed in our previous work on how social learning influences openness to new information. The paper is now under review at Plos ONE.
Part of the Cultural Evolution Seminar Series at Brooklyn College
Abstract: Human decision models often begin with individual, cost-benefit analyses as the basic behavior, with any social influence as a secondary add-on. Thisoften underestimates social influence among humans, whose brains have actually evolved to handle social relations. In fact, a better starting point in many casesmay be to assume that people base their choices (consciously or not) primarily on the decisions of those around them. As captured by experiments and simpleevolutionary drift models, undirected social influence introduces an irrationality and unpredictability to collective behavior, with implications for anthropology,psychology and economics.
Alex Bentley is Reader in Anthropology at Durham University, where he is co-founder of the Centre for the Coevolution of Biologyand Culture, and Deputy Director of a 5 year project on ‘Tipping Points: Mathematics, Metaphors and Meanings”, funded by theLeverhulme Trust.
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