Cultural evolution in Vietnam's early 20th century: a Bayesian networks analysis of Franco-Chinese house designs

TL;DR

This paper employs Bayesian networks and MCMC methods to analyze the influence of cultural factors, especially Buddhism, on Vietnamese house facades in early 20th century Hanoi, revealing significant cultural transmission patterns.

Contribution

It introduces a Bayesian network approach combined with MCMC to study cultural evolution through architectural features, providing a novel quantitative analysis in this context.

Findings

Buddhism significantly influences house facade decorations.

Bayesian models identify strong probabilistic dependencies related to cultural elements.

Robustness of models confirmed through Hamiltonian MCMC analysis.

Abstract

The study of cultural evolution has taken on an increasingly interdisciplinary and diverse approach in explicating phenomena of cultural transmission and adoptions. Inspired by this computational movement, this study uses Bayesian networks analysis, combining both the frequentist and the Hamiltonian Markov chain Monte Carlo (MCMC) approach, to investigate the highly representative elements in the cultural evolution of a Vietnamese city's architecture in the early 20th century. With a focus on the fa\c{c}ade design of 68 old houses in Hanoi's Old Quarter (based on 78 data lines extracted from 248 photos), the study argues that it is plausible to look at the aesthetics, architecture and designs of the house fa\c{c}ade to find traces of cultural evolution in Vietnam, which went through more than six decades of French colonization and centuries of sociocultural influence from China. The in-depth technical analysis, though refuting the presumed model on the probabilistic dependency among the variables, yields several results, the most notable of which is the strong influence of Buddhism over the decorations of the house fa\c{c}ade. Particularly, in the top 5 networks with the best Bayesian Information criterion (BIC) scores and p<0.05, the variable for decorations (DC) always has a direct probabilistic dependency on the variable B for Buddhism. The paper then checks the robustness of these models using Hamiltonian MCMC method and find the posterior distributions of the models' coefficients all satisfy the technical requirement. Finally, this study suggests integrating Bayesian statistics in social sciences in general and for study of cultural evolution and architectural transformation in particular.