Computational Cultural Sciences

The explosion of cultural data, coupled with the recent advances in machine learning, natural language processing, big data and cognitive science, offers a unique opportunity to better understand the human mind and human culture.

In 2021, I have created the Computational Cultural Sciences group which now includes with Valentin Thouzeau, Andrei Mogoutov, Charles de Dampierre, Edgar Dubourg and Zhong Ying.

Baumard, N., Huillery, E., Hyafil, A. and Safra, L. (2022) The cultural evolution of love in history, Nature Human Behavior (Supplementary material, supplementary review, data and code here)

Dubourg, E., Thouzeau, V., de Dampierre, C., & Baumard, N. Exploratory preferences explain the cultural success of imaginary worlds in modern societies.

Hyafil, A. & Baumard, N. (2022) Evoked and Transmitted Culture models: Using bayesian methods to infer the evolution of cultural traits in history, Plos One

Baumard, N., Huillery, E. and Zabrocki, L. (in review) The Economic Origins of Ascetic Values : Evidence from Medieval Europe

Martin, M. & Baumard, N. (2020) The rise of prosociality in fiction preceded democratic revolutions in Early Modern Europe, PNAS

Safra, L., Chevallier, C., Grèzes, J., Baumard, N. (2020) Tracking the rise of trust in history using machine learning and paintings, Nature Communication

De Courson, B. & Baumard, N., Quantifying the Scientific Revolution (heatmaps of scientific productivity in the 16th c., 17th c. and 18th c.) SocArXiv, 6 Dec. 2019. Web.

Jacquet, P.O., Pazhoohi, F., Findling C., Mell, H., Chevallier, C., Baumard, N. (in press) Predictive multivariate modelling of religiosity in 295 000 individuals from WEIRD and non-WEIRD populations, Humanities and Social Sciences Communications

Baumard, N., Hyafil, A. Morris, I., and Boyer, P., (2015) Increased affluence explains the emergence of ascetic wisdoms and moralizing religions. Current Biology, 25(1), 10-15. (See press coverage in Science)