pnas | An outstanding open problem is whether collective social phenomena
occurring over short timescales can systematically reduce
cultural heterogeneity in the long run,
and whether offline and online human interactions contribute differently
to the process.
Theoretical models suggest that short-term
collective behavior and long-term cultural diversity are mutually
excluding, since
they require very different levels of
social influence. The latter jointly depends on two factors: the
topology of the underlying
social network and the overlap between
individuals in multidimensional cultural space. However, while the
empirical properties
of social networks are intensively
studied, little is known about the large-scale organization of real
societies in cultural
space, so that random input specifications
are necessarily used in models. Here we use a large dataset to perform a
high-dimensional
analysis of the scientific beliefs of
thousands of Europeans. We find that interopinion correlations determine
a nontrivial
ultrametric hierarchy of individuals in
cultural space. When empirical data are used as inputs in models,
ultrametricity has
strong and counterintuitive effects. On
short timescales, it facilitates a symmetry-breaking phase transition
triggering coordinated
social behavior. On long timescales, it
suppresses cultural convergence by restricting it within disjoint
groups. Moreover,
ultrametricity implies that these results
are surprisingly robust to modifications of the dynamical rules
considered. Thus
the empirical distribution of individuals
in cultural space appears to systematically optimize the coexistence of
short-term
collective behavior and long-term cultural
diversity, which can be realized simultaneously for the same moderate
level of
mutual influence in a diverse range of
online and offline settings.
