Cultural drift, indirect minority influence, network structure, and their impacts on cultural change and diversity.

Abstract

The present research investigates how psychological mechanisms and social network structures generate patterns of cultural change and diversity. The two psychological mechanisms studied here are cultural drift and indirect minority influence; the former is parameterized by an error rate e) and the latter by a leniency threshold (k). The patterns of cultural change are examined in terms of magnitude (small vs. large), speed (gradual vs. rapid), and frequency (frequent vs. rare). Diversity and polarization in a society are examined in terms of global cultural variation (inverse Simpson index) and local neighborhood difference (Hamming distance). Key findings are that in networks with high connectivity or local community structures (complete, scale-free, random, and modular networks) cultural drift can produce a rapid, large, and rare pattern of cultural change (punctuated equilibrium), whereas in lattice or small world networks, it produces a more gradual change pattern. Indirect minority influence robustly produces a gradual, small, and frequent pattern of cultural change (gradualism) across various network structures. When cultural change occurs in social networks that have a modular community structure, indirect minority influence generates a regime of cultural diversity whereas cultural drift generates a polarized regime. Finally, cultural drift and indirect minority influence generate distinct tipping points for social change in different network structures, but prediction of whether and when cultural change emerges is difficult at tipping points in both cases.

Rebiasing: Managing automatic biases over time

“…Our work thus answers calls to explore the role of intuition and affect in decision making over time (see George and Dane, 2016 ). Via the computational experiments used in the present research, we can point to the plausibility of phenomena that would be otherwise difficult to observe empirically (e.g., Epstein, 1999 ; Gray et al, 2014 ; Jung et al, 2021 ; Schaller and Muthukrishna, 2021 ).…”

“…Similar to Jung et al (2021) we illustrate the logic of the search process with an algorithm. However, our algorithm does not have a defined stopping point.…”

Minority Influence: An Agenda for Study of Social Change

“…More recently, social change has been examined as a function of two factors: Indirect minority influence, defined as attitudinal change on culturally relevant issues different from but related to the focal issue of minority advocacy, and cultural drift, defined as mistakes in copying culturally relevant attributes due to small errors in the learning and memory processes. Computational modeling and simulations suggest that indirect minority influence yields gradual social change and diversity, whereas cultural drift generates rapid social change and polarization in a society ( Jung et al, 2021 ). None of the proposed models, however, has been tested empirically outside of computational simulations.…”

The psychology of cultural change: Introduction to the special issue.

“…These pieces capture a range of theoretical perspectives that have been brought to bear on how and why cultures change over time, including insights from evolutionary psychology (Jackson et al, 2021; Kusano & Kemmelmeier, 2021; Pan et al, 2021), behavioral ecology (Rotella et al, 2021), cultural evolution (Schaller & Muthukrishna, 2021), and socioecological psychology (Buttrick & Oishi, 2021). The special issue also highlights the diversity of methodological approaches in this emerging field ranging from computational modeling (Jung et al, 2021; Schaller & Muthukrishna, 2021; Pan et al, 2021), to machine learning (Sheetal & Savani, 2021; Stavrova et al, 2021), to time series analyses (Charlesworth & Banaji, 2021; Chan et al, 2021; Götz et al, 2021; Kusano & Kemmelmeier, 2021; Rotella et al, 2021).…”

“…Finally, the special issue includes articles that tackle the “How”—attempts to model and capture the broad processes involved in cultural change writ large. These include studies on the dynamics of collective memory and forgetting (Candia & Uzzi, 2021), investigations of how the meaning of concepts can change over time (Haslam et al, 2021), and work modeling the likelihood and speed of cultural change as a function of factors like cultural drift, interpersonal influence, and network characteristics (Jung et al, 2021; Schaller & Muthukrishna, 2021).…”