How Communities Scale into Civilizations: The Diffusion of Culture Across Historical Networks

We analyze structure and function in the network design of historical regimes to build a theory for the development of societies and states from endogenous mechanisms of social change. We use historical evidence from China and Western Europe to show how their respective network structures evolved independently but share a global property: both are small world, meaning that any node in the network can reach any other node by a small number of steps. Probing the variations in network topologies and their role in diffusion and scaling, we account for differences in formal institutions, interpersonal trust, cultural norms, and moral protocols. Electronic copy available at: https://ssrn.com/abstract=3854099 2 INTRODUCTION For decades, the economic models that tested cooperation predicted that it would only endure in groups that developed social norms of commitment, trust, and reciprocity. But as Mathew Jackson noted, and what still holds, those predictions invariably have drawn from models that address small groups of agents and ignore the more profound questions of how communities build out networks into historical regimes with the capacity to create bonds extending beyond kinship and lineage. How, for example, did the cultural and historical assemblages of Europe and China form and survive millennia? How did they become capable of coordinating complex, multilayered functions of leadership succession, property transfer, the mobilization of revenue and arms, and the development of codes of conduct and moral persuasion? The advent of agent modeling on a massive scale enables network analysis to extend its range to such topics as “the randomness that governs the opportunity for people to form relationships, as well as the incentives underlying the choices of which relationships appear and endure” (Jackson 2008). Scholars who focus on questions of long-term cultural change offer rival explanations based in economic geographic, demographic, institutional, or political interpretations. In this paper, we examine the economic trajectories of China and Europe through an exploration of their respective network structures and information-sharing mechanisms. Discoveries in complex systems research have shifted the focus of social network analysis from single-node centrality and small-graph connection mapping to consideration of the large-scale properties of the graph (the network structure) itself. We can now study how network mechanisms enable system-level connectivity and the diffusion of innovation for large-scale cooperation—and how the systems themselves coevolve with the communities they support. As we search for the network mechanisms that allow individuals and communities to engage in large-scale cooperation, we also want to find sources in network structures that help explain the diffusion of innovation. In this way, we can explore not only the shared properties of China and Europe, but also the varieties of social organization that shaped their respective “innovation cultures” and permitted them to construct networks of scale.1 1 Complex networks are explored in Vega-Redondo (2007); Newman (2003); and Newman, Barabasi, and Watts (2006). Electronic copy available at: https://ssrn.com/abstract=3854099 3 A critical element of cooperation and diffusion of innovation in any network is the connectivity from one community to another. It is easy to see how modern information technologies link to the dynamics of interdependence within and among nations. Information sharing is everywhere around us. Yet in many sparsely governed premodern polities, it was also possible for beliefs and institutions representing a unity of the collective to be woven together. Diffusion mechanisms also permitted the long-lived historical regimes in Europe and China to scale from their original tribal/village networks into broader communities, kingdoms, states, nations, and ultimately civilizations.2 We propose that long-enduring civilizations, states, and societies are of a universal class of systems whose network structures comprise many differing patterns of intersections but which share a global property: their ability to connect the parts—the hamlets, villages, and townships— and coordinate activities among them, no matter how remote or sparsely administered, through information-sharing networks that allow a collective memory and sense of common purpose. They are giant webs of communication in which, at some fundamental level, every node is processing information from the other nodes that form the system. We turn to network science to explore how this information sharing came about in the absence of modern communication technologies.3 The network structures, or topologies, of Western Europe and China evolved independently yet as small-world networks any node in the network can reach any other node by a small number of steps. Their small-world connectivity itself shares another property: in both, connectivity was historically embodied in a system of rule by hereditary kingship. As we examine differences in the two network structures, we will see how the diffusion of information within them afforded different advantages to each. In Section 1, we will explore how durable small-world networks come into being, their evolutionary convergence, and why they hold advantages for building the foundations of sustained social cooperation beyond the affinities of kinship and lineage. This section describes how societal structures network into complexity and includes descriptions and specific definitions of small and large worlds, concluding with a discussion of the role small-world 2 Both early Europe and China sustained complex state-based social capacity that far exceeded the longevity of the Mongol, Ottoman, or Mughal empires found in the center of Eurasia. 3 Information technologies link to broader national interest and international standing in contemporary political economy in The Uses and Abuses of Weaponized Interdependence (Drezner, Farrell, and Newman 2021). Electronic copy available at: https://ssrn.com/abstract=3854099 4 connectivity plays in formation of long-lived historical regimes. Section 2 addresses the systemlevel structures in the West and China and includes the role played by bridge nodes. The next two sections discuss specific social institutions that support connectivity: Section 3 discusses an institution that China and the West shared, hereditary succession; and Section 4 examines institutional differences, such as religion, as well as social mobility, elite recruitment, and local governance. Section 5 explores how these network structures can also account for differing innovation systems, with inferences for the different economic structures of the two regimes. Section 6 discusses the network sources of interpersonal social trust and the embeddedness of cultural norms. The conclusion discusses how longstanding differences in their network topologies may continue to shape the evolution of these two societies, taking into particular consideration the fact that China lacks any historical parallel to the trust-building networks and institutions that were fundamental to Western Europe’s development. 1. CONNECTIVITY: HOW SYSTEM TOPOLOGY ENABLES COMMUNITIES TO “NETWORK” INTO COMPLEXITY The original human communities were small-scale networks, built on kinship and tribal affiliation. This homophily—the tendency to associate only with similar people—also enabled them to survive (McPherson, Smith-Lovin, and Cook 2001). Most ethnographic descriptions of early human settlements generalize that when homophily is prevalent, there also arise distinct traditions, e.g., particular gods, laws, and cultural norms. For example, some societies emphasize status by descent, while others emphasize achievement. Without shared beliefs, moral codes, or rules, the communities refrain from large-scale cooperation. Many primitive societies also maintained highly impermeable internal barriers that reinforced stratification of members, further resulting in the disconnectedness of the whole (Flannery and Marcus 2012; Root 2020, 115–19). Yet homophily also made the greater system they inhabited a “large world,” a theoretical term reflecting the reality that communications and interactions were primarily local and isolated. When depicted on a graph, a large-world network exhibits a high clustering coefficient, but low network connectivity (Michelitsch et al. 2019, 6–7). 4 Thus, a large-world network can be 4 The links of small-scale networks usually show a relatively even distribution to each other and aggregate into something that resembles the network of streets or subway stations in a city, roads in the countryside, or pixels in a digital image. A network of airline flights, by contrast, is small world in that it features many connected hubs that shorten paths and improve system-wide coordination. Electronic copy available at: https://ssrn.com/abstract=3854099 5 made up of nodes that cluster in sizable groupings, but each node will link to only a few nearby nodes, and communities (hubs) do not link to one another. There are no long paths to reduce distances between various hubs within the entire structure. FIGURE 1. Three diagrams of large-world networks: Note that despite a system’s dense local connectivity, many steps will be necessary along short path lengths between adjacent nodes to move information across the system, creating a long average path length. Where there are no long paths, there is long average path length, which is another system-level property of large worlds. Path length is not a measure of length per se, but of efficiency. It determines how rapidly and through what channels information is distributed across the wider network. In a large world, information passes along short paths, from one node to the next to the next. Transmission across the entire system may require thousands of interactions between individual nodes—ergo, a long path lengt