Experimental evidence for scale-induced category convergence across populations

Abstract

Individuals vary widely in how they categorize novel and ambiguous phenomena. This individual variation has led influential theories in cognitive and social science to suggest that communication in large social groups introduces path dependence in category formation, which is expected to lead separate populations toward divergent cultural trajectories. Yet, anthropological data indicates that large, independent societies consistently arrive at highly similar category systems across a range of topics. How is it possible for diverse populations, consisting of individuals with significant variation in how they categorize the world, to independently construct similar category systems? Here, we investigate this puzzle experimentally by creating an online “Grouping Game” in which we observe how people in small and large populations collaboratively construct category systems for a continuum of ambiguous stimuli. We find that solitary individuals and small groups produce highly divergent category systems; however, across independent trials with unique participants, large populations consistently converge on highly similar category systems. A formal model of critical mass dynamics in social networks accurately predicts this process of scale-induced category convergence. Our findings show how large communication networks can filter lexical diversity among individuals to produce replicable society-level patterns, yielding unexpected implications for cultural evolution.

Probabilistic social learning improves the public’s judgments of news veracity

“…Together, these results suggest that fact-checkers and social media organizations can better mitigate polarization and the spread of misinformation by using more probabilistic representations of news veracity. More broadly, these results contribute to a growing body of work on networked crowdsourcing, which identifies the conditions under which communication networks can enhance the consistency and accuracy of classification systems for a range of applications [20][21][22][23]37].…”

“…For example, it may be that individuals' mental representations of news veracity are probabilistic in nature, such that binary signaling prevents them from expressing improvements in their internal beliefs during communication [34][35][36]. Future work may also find that, since individual cognition combines both categorical and probabilistic judgments, the optimal communication modality for social learning involves a combination of categorical and binary signaling [34][35][36][37]. We anticipate that future research will benefit from exploring these questions.…”

Exposure to the Views of Opposing Others with Latent Cognitive Differences Results in Social Influence—But Only When Those Differences Remain Obscured

“…This study also adds to a growing literature that has identified distinct facets of cognitive diversity in groups and new ways of measuring it-ranging from mental models (Carley and Palmquist 1992) to cognitive styles (Aggarwal and Woolley 2019) to schemas of poverty (Hunzaker and Valentino 2019) to linguistic categories (Guilbeault, Baronchelli, and Centola 2021) to discursive diversity (Lix, Goldberg, Srivastava, and Valentine 2021). Although our approach in this study focused on cognitive heterogeneity at the dyadic level, it can be readily extended to measure cognitive diversity in larger social groups.…”

Revision, Reclassification, and Refrigerators1

“…Shepherd (2010), for example, has shown how the internalization of classification systems at the level of personal culture is shaped by, but also partially decoupled from, external classification systems. Guilbeault, et al (2021) explore how people converge on shared ways of classifying ambiguous tokens (cf Hebart et al 2020), specifically how groups of people come to share the same types over multiple iterations of coordination, in line with research on the development and maintenance of "arbitrary traditions" (e.g., Jacobs and Campbell 1961;Zucker 1977). In this paper, by extension, we consider how established types may change.…”