Expect the Unexpected? Testing for Minimally Counterintuitive (MCI) Bias in the Transmission of Contemporary Legends: A Computational Phylogenetic Approach

Abstract

In this study, we use computational methods for analyzing cultural transmission to examine the role of cognitive selection pressures on the evolution of narratives, the first use of computational phylogenetic analysis in the study of contemporary legends. It has been suggested that a number of biases in transmission may alter the content and structure of narrative so as to maximize how transmittable it is. One bias that has attracted much attention is Boyer’s minimally counterintuitive (MCI) bias, which suggests that a cognitively optimal number of counterintuitive concepts increase the salience and, therefore, the transmission of a narrative. Previous research has used traditional folklore and religious texts to examine this bias and a cognitively optimum number of 1–2 or 2–3 counterintuitive concepts has been suggested. The present research uses the legend of “Bloody Mary,” a contemporary (or urban) legend with MCI elements in a computational phylogenetic analysis to examine the influence of MCI on cultural transmission and evolution. Counterintuitive and intuitive concepts were found to be equally stable in transmission, suggesting that MCI bias may function on the narrative as a whole, rather than individual concepts within it.