Cultural traits—such as the ideas, beliefs, behaviors, customs, and practices defining a society—are shaped by two opposing forces: conformity, which is the tendency to align with others, and anti-conformity, the decision to intentionally deviate. A new model to explore this intricate interaction may provide insights into societal issues like political polarization, cultural fads, and the spread of false information.
Cultural traits—such as the ideas, beliefs, behaviors, customs, and practices defining a society—are shaped by two opposing forces: conformity, which is the tendency to align with others, and anti-conformity, the decision to intentionally deviate. A new model to explore this intricate interaction may provide insights into societal issues like political polarization, cultural fads, and the spread of false information.
A recent study featured in the Proceedings of the National Academy of Sciences presents this innovative approach. With a mathematical model, SFI Complexity Postdoctoral Fellow Kaleda Denton, along with Stanford University colleagues—former SFI Post-baccalaureate Fellow Elisa Heinrich Mora, SFI External Professor Marcus Feldman, and Michael Palmer—build on earlier research to provide a more accurate depiction of how conformist and anti-conformist inclinations influence the sharing of cultural traits across populations.
“The goal of this research was to develop a better mathematical model for how people make decisions in real life,” Denton explains. “If we succeed, we can predict outcomes for larger populations, such as 10,000 individuals, over extended periods.”
Conventional models of conformity typically suggest that individuals tend to conform to the average or “mean” trait of a population. This concept is effective when the most prevalent traits cluster around this mean, such as typical work hours or food portion sizes. However, it fails when, for instance, many individuals align with extreme positions on a political spectrum, while the mean is located in the center.
To fill this gap, the researchers formulated a model that incorporates trait clustering. In this model, individuals conform by adopting traits that are more closely grouped together (for example, variations of extreme left political views), rather than embracing the mean trait (such as centrist opinions). Conversely, anti-conformists make conscious choices to differentiate themselves from their peers, fostering polarization.
Through computer simulations, the team explored how traits evolve across populations through generations. Conformity often resulted in groups coalescing around certain traits, but not necessarily the average trait. Conversely, anti-conformity led to a U-shaped distribution, with individuals gravitating towards extremes and leaving the center less populated.
An important discovery was that populations seldom converge to a single trait unless an unrealistic scenario of perfect imitation is assumed. Instead, even minor differences in how individuals perceive or adopt traits contribute to enduring diversity.
“These results mirror what we see in real life, where cultural practices and ideologies do not merely average out but show considerable diversity,” Denton states.
The research further contests the belief that conformity inevitably leads to uniformity. The model indicates that in specific circumstances, conformity can preserve diversity, while anti-conformity intensifies polarization.
Denton envisions wide-ranging implications for this study. “This framework could shed light on voting behaviors, social media dynamics, or how groups estimate values,” she notes. “It provides a lens through which to understand how individual choices can accumulate into broader societal patterns, whether that is consensus or polarization.” Upcoming studies could test this model against real-world data.
“We’re eager to see how this framework performs across different contexts,” Denton said. “Our ultimate aim is to grasp how individual choices can shape entire populations over time.”
