How do societies develop categories for continuous sets of novel phenomena, as in the domains of art and technology?Seminal work in the nativist tradition argues that given the same stimuli, people can independently produce the samecategories as a result of universal cognitive constraints. These constraints are said to account for cross-group coherence,where distinct communities and cultures have been shown to arrive at highly similar categories. Cross-group coherence iswidely seen as incompatible with functionalism, which holds that categories are defined through communication, leadingto divergent category systems. Here, we use an experiment to demonstrate that communication can generate either thedivergence or convergence of category systems, depending on the size of the social network (2, 6, 8, 24, and 50). We findthat large social networks amplify population biases, where a subset of slightly more frequent words become exponentiallymore likely to spread as network size increases.

Most aspects of our lives are governed by large, highly developed institutions that integrate several governance tasks under one authority structure. But theorists differ as to the mechanisms that drive the development of such concentrated governance systems from rudimentary beginnings. Is the emergence of integrated governance schemes a symptom of consolidation of authority by small status groups? Or does integration occur because a complex institution has more potential responses to a complex environment? Here we examine the emergence of complex governance regimes in 5,000 sovereign, resource-constrained, self-governing online communities, ranging in scale from one to thousands of users. Each community begins with no community members and no governance infrastructure. As communities grow, they are subject to selection pressures that keep better managed servers better populated. We identify predictors of community success and test the hypothesis that governance complexity can enhance community fitness. We find that what predicts success depends on size: changes in complexity predict increased success with larger population servers. Specifically, governance rules in a large successful community are more numerous and broader in scope. They also tend to rely more on rules that concentrate power in administrators, and on rules that manage bad behavior and limited server resources. Overall, this work is consistent with theories that formal integrated governance systems emerge to organize collective responses to interdependent resource management problems, especially as factors such as population size exacerbate those problems.

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.

How do solution strategies spread in teams? Inspired by the 80s sci-fi movie Close encounters of the third kind, weset up a networked multiplayer game where participants had to signal peace to invading aliens from space by playingmusic. In each round of the game, participants were matched in dyads and through chat had to jointly construct a four-tone melody. Melodies translated to points according to a rugged landscape score system. We compared three networktopologies: a lattice network (participants only play with immediate neighbours), a fully connected network, and dyads.Furthermore, we manipulated the nature of the problem being either open-ended or with fixed solutions by making themaximum possible score known or not. With known maximum score, lattice networks show an advantage with increasedpropensity to explore and diffusion of good solutions, compared to fully connected networks. No effects are observedwhen the maximum score is unknown.