Reconciling long-term cultural diversity and short-term collective social behavior

Abstract

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 longterm 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.collective social phenomena | homophily | social influence | sociophysics | ultrametricity H ow a society spontaneously organizes macroscopically from the microscopic, uncoordinated behavior of individuals is one of the most studied and exciting problems of modern science (1-3). Collective social phenomena are systematically observed in several aspects of everyday life, including the onset of large-scale popularity and fashion [both offline (4) and online (5-7)], the existence of large speculative bubbles and herding behavior in financial markets (8-10), the spontaneous emergence of order in traffic and crowd dynamics (11), the properties of voting dynamics (4, 12), the structure of countrywide communication networks (3,13,14), individual specialization and the spreading of cooperation, habits, fear, gossip, rumors, etc. (2,11,15). When collective phenomena occur, large parts of a population turn out to be globally correlated or synchronized as a result of the combination of many local interactions, even if no centralized mechanism takes place. Importantly, the collective outcome is different from a mere superposition of noninteracting individual behaviors, and contrasts the "representative agent" scenario ofte...

Signs of universality in the structure of culture

“…It became apparent that the final state is rather sensitive to the initial state. In particular, an initial state constructed from an empirical social survey behaved significantly different from an initial state that was generated in a uniformly random way [23]. This implies that cultural dynamics is sensitive to the structure inherent in empirical data.…”

“…Thus, if the cultural vectors in the initial state correspond to real individuals, the outcome of social influence models can be used as a quantitative tool for gaining insight about how real individuals are distributed in cultural space, and indirectly about cultural dynamics in the real world, since the initial cultural state can be regarded as a partial snapshot of the real world dynamics. This is, to a great extent, the perspective of the research presented here, which makes use of a quantitative technique developed in reference [23] On one hand, this technique incorporates the idea of social-influence cultural dynamics, which is encoded by a measure of long-term cultural diversity (LTCD), which makes use of an Axelrod-type model [13] of cultural dynamics with a minimal set of ingredients. The LTCD quantity estimates the extent to which discrepancies between opinions survive after a long period of cultural dynamics governed by consensus-favoring social influence, in the absence of any other process.…”

“…Taking a somewhat different perspective, references [23,24] explored alternative classes of initial conditions, trying instead to understand the effect that the initial state has on the dynamics and on the final state. It became apparent that the final state is rather sensitive to the initial state.…”

“…Each of the three cultural states induces, in the LTCD-STCB plot, a curve parametrised by the bounded confidence threshold. In reference [23], for the random cultural state, the curve was such that at least one of the two quantities attained a close-to-minimal value for any value of the bounded confidence threshold ω, meaning that STCB and LTCD were mutually exclusive. This apparently called for a more complicated description or otherwise suggested a paradox, since real-world societies seem to allow for both short-term collective behavior and long-term cultural diversity.…”

“…The current study is dedicated to checking the robustness of the LTCD-STCB behavior identified in reference [23] across different empirical data sets. As shown in Section 4, this behavior appears to be universal, robust across geographical regions and independent of the details of the feature-feature correlation matrix.…”