Cultural traits (the information, beliefs, behaviors, customs, and practices that shape the character of a population) are influenced by conformity, the tendency to align with others, or anticonformity, the choice to deliberately diverge. A new way to model this dynamic interaction could ultimately help explain social phenomena such as political polarization, cultural trends, and the spread of misinformation.
A study published in the Proceedings of the National Academy of Sciences describes this novel approach. By presenting a mathematical model, SFI Complexity Postdoctoral Fellow Kaleda Denton, along with her Stanford University colleagues (former SFI Graduate Fellow Elisa Heinrich Mora, SFI External Professor Marcus Feldman, and Michael Palmer) expand previous research to offer a more realistic representation of how conformist and anticonformist prejudices shape the transmission of cultural traits through a population.
“The idea behind this research was to find a better way to mathematically represent how individuals make decisions in the real world,” says Denton. “If we can do that, then we can scale things up to see what would happen in a population of 10,000 people in the long term.”
Traditional conformity models often assume that individuals gravitate toward the average or “bad” trait in a population. This concept works well if the most popular traits are close to this average, as may be the case, for example, with work hours or food portion sizes. However, the average is a poor indicator of popularity in other cases; For example, if most people are on the far left or far right of a political spectrum, but the average is in the center.
To address this gap, the authors designed a model that incorporates trait clustering. In this model, individuals conform by adopting traits that are more clustered (e.g., variations of a far-left political belief) than the average trait of the population (e.g., centrist views). Anticonformists, on the other hand, deliberately distance themselves from the traits of their peers, creating polarization.
Using computer simulations, the team analyzed how traits spread among populations over multiple generations. Conformity often led to groups clustering around specific traits, but not necessarily the average. Anticonformism created a markedly different pattern: a U-shaped distribution, with individuals clustered at the extremes and leaving the center sparsely populated.
A significant finding was that populations rarely converge on a single trait unless the unrealistic assumption of perfect behavioral copying is imposed. Instead, even small variations in the way individuals interpret or adopt traits result in persistent diversity.
“These results align with what we observe in the real world, where cultural practices and ideologies do not simply average out but maintain significant variation,” Denton says.
The research also challenges the notion that conformity always leads to homogeneity. The model shows that, under certain conditions, conformity can sustain diversity, while nonconformity amplifies polarization.
Denton sees broad implications for the study. “This framework could help explain voting behavior, social media trends, or even how people estimate values in group settings,” he says. “It offers a way to understand how individual decisions add to social patterns, whether through consensus building or polarization.” This model can be tested with real-world data in future studies.
“We are excited to see if this framework works in different scenarios,” Denton said. “The ultimate goal is to understand how individual choices influence entire populations over time.