The Small World of Canadian Capital Markets: Statistical Mechanics of Investment Bank Syndicate Networks, 1952-1989

Networks are ubiquitous; they surround us; we engage dozens of them daily. The global economy is a network of national economies, which are networks of markets, which in turn are networks of firms, which in turn are networks of people. Increasingly, the technologies and social institutions on which we depend are explicitly engineered as networks. Our understanding of networks, however, has not kept up with our dependence on them.

What is a network? A network is essentially anything that can be represented by a graph: a set of points (also genetically called nodes or vertices), connected by links (edges, ties) representing some qualitative relationship. In social networks, the nodes are people or groups of people, "actors" in the jargon of the sociology, with some pattern of interactions or "ties" between them. A social network, then, is a set of people or groups of people (e.g., organizations) linked by acquaintance, friendship, political alliance, professional collaboration, or business relationships.

Network analysis currently forms the core of the "new economic sociology," which rests on the argument that networks generate and structure markets, creating pathways to sources of information and resources (Smelser & Swedberg, 1994). Social networks have, however, been the subject of both empirical and theoretical study in the social sciences for over 50 years, partly because of inherent interest in patterns of human interaction, but also because their structure has important implications for the spread of information, ideas, and disease, as well as social influence and inequality (Smelser & Swedberg). It is clear, for example, that variation simply in the average number of acquaintances that individuals have can substantially influence the propagation of a rumour, fad, fashion, joke, or this year's strain of the flu.

Traditionally, sociologists have viewed networks as static objects, "as given contexts for action" (Madhavan, Koka, & Prescott, 1998, p. 439). More recently, following a surge in interest in network structure among mathematicians and physicists, partly as a result of studies of the Internet and the World Wide Web and partly the broader movement toward research on complex systems, a growing stream of research has investigated the statistical properties of networks and methods for modeling networks. In this work, networks are conceived as dynamic systems that self-assemble and evolve in time through the addition and removal of actors and ties. The techniques of statistical mechanics, it turns out, are well suited to the study of networks. Indeed, graph theoretic analyses have permitted comparison of seemingly unrelated networks, leading to the exposure of deep similarities among social, biological, and technological n...

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