Suchergebnisse

The Connected City explores how thinking about networks helps make sense of modern cities: what they are, how they work, and where they are headed. Cities and urban life can be examined as networks, and these urban networks can be examined at many different levels. The book focuses on three levels of urban networks: micro, meso, and macro. These levels build upon one another, and require distinctive analytical approaches that make it possible to consider different types of questions. At one extreme, micro-urban networks focus on the networks that exist within cities, like the social relationships among neighbors that generate a sense of community and belonging. At the opposite extreme, macro-urban networks focus on networks between cities, like the web of nonstop airline flights that make face-to-face business meetings possible. This book contains three major sections organized by the level of analysis and scale of network. Throughout these sections, when a new methodological concept is introduced, a separate 'method note' provides a brief and accessible introduction to the practical issues of using networks in research. What makes this book unique is that it synthesizes the insights and tools of the multiple scales of urban networks, and integrates the theory and method of network analysis.

AbstractThe Strength of Weak Ties is among the most influential social theories of the past 50 years. However, its prediction that weak ties are especially useful for obtaining novel information is sometimes not supported. To understand why, I investigate whether social networks typically satisfy the theory's assumptions, and whether the theory's prediction is robust to violations of its assumptions. First, examining a diverse corpus of 56 empirical social networks, I show that empirical social networks (nearly) satisfy some but not all of the theory's assumptions. Second, using a simulation of information diffusion, I show that the predicted utility of weak ties is not robust to violations of these assumptions. When the assumptions of the theory are violated, as is common in social networks, access to novel information depends on bridging ties, regardless of their strength. Moreover, when they exist, strong bridges (i.e., bridges with high bandwidth) are more useful than weak bridges (i.e., bridges with low bandwidth). I conclude by recommending that research applying this theory should first consider whether its assumptions are satisfied, and that a tie's strength and bridgeness should be measured and modeled independently.

This commentary responds to Gade in 'When is it justified to claim that a practice or policy is evidence-based? Reflections on evidence and preferences'(Evidence & Policy, 20(2): 244–253, DOI: 10.1332/174426421X16905606522863).

AbstractCollecting network data directly from network members can be challenging. One alternative involves inferring a network from observed groups, for example, inferring a network of scientific collaboration from researchers' observed paper authorships. In this paper, I explore when an unobserved undirected network of interest can accurately be inferred from observed groups. The analysis uses simulations to experimentally manipulate the structure of the unobserved network to be inferred, the number of groups observed, the extent to which the observed groups correspond to cliques in the unobserved network, and the method used to draw inferences. I find that when a small number of groups are observed, an unobserved network can be accurately inferred using a simple unweighted two-mode projection, provided that each group's membership closely corresponds to a clique in the unobserved network. In contrast, when a large number of groups are observed, an unobserved network can be accurately inferred using a statistical backbone extraction model, even if the groups' memberships are mostly random. These findings offer guidance for researchers seeking to indirectly measure a network of interest using observations of groups.

AbstractShared memberships, social statuses, beliefs, and places can facilitate the formation of social ties. Two-mode projections provide a method for transforming two-mode data on individuals' memberships in such groups into a one-mode network of their possible social ties. In this paper, I explore the opposite process: how social ties can facilitate the formation of groups, and how a two-mode network can be generated from a one-mode network. Drawing on theories of team formation, club joining, and organization recruitment, I propose three models that describe how such groups might emerge from the relationships in a social network. I show that these models can be used to generate two-mode networks that have characteristics commonly observed in empirical two-mode social networks and that they encode features of the one-mode networks from which they were generated. I conclude by discussing these models' limitations and future directions for theory and methods concerning group formation.

Abstract
The fields of social network analysis and network science have recently undertaken efforts to address issues of gender diversity and representation. However, despite these important efforts, subtle threats to representation are likely to persist. I use a 2023 global survey of 260 network researchers to show that men rate themselves as having more expertise with networks than women. This is troubling because, to the extent that women believe they lack the expertise to be considered for awards or collaboration opportunities, it can impede other efforts to diversify the field. I conclude by discussing some possible explanations for this finding and some possible strategies for addressing its consequences.

Abstract
Political network data can often be challenging to collect and clean for analysis. This article demonstrates how the incidentally and backbone packages for R can be used together to construct networks among legislators in the US Congress. These networks can be customized to focus on a specific chamber (Senate or House of Representatives), session (2003 to present), legislation type (bills and resolutions), and policy area (32 topics). Four detailed examples with replicable code are presented to illustrate the types of networks and types of insights that can be obtained using these tools.

AbstractMany studies have attempted to determine whether an observed network exhibits a so-called "small-world structure." Such determinations have often relied on a conceptual definition of small worldliness proposed by Watts and Strogatz in their seminal 1998 paper, but recently several quantitative indices of network small worldliness have emerged. This paper reviews and compares three such indices—the small-world quotient (Q), a small-world metric (ω), and the small-world index(SWI)—in the canonical Watts–Strogatz re-wiring model and in four real-world networks. These analyses suggest that researchers should avoid Q, and identify considerations that should guide the choice between ω and SWI.

Concerns about the negative externalities of air transport suggest it is important to consider the sustainability of growth in demand for air transport. However, there is little agreement on how the sustainability of demand should be evaluated. In this paper, I draw on the extensive literature on allometric scaling in biology, which examines animals' demand for calories, to provide a novel framework for evaluating the sustainability of cities' demand for air transport service. Viewing cities as analogous to organisms and airline passengers as analogous to life-sustaining resources, I focus on two questions. First, at what rate do cities metabolise passengers, that is, how many airline passengers does it take to fuel a city of a given size? Second, does this metabolic rate differ for business and leisure passengers, which represent different kinds of urban resources? Using data on airline passenger movement between 103 US metropolitan areas in each year from 1993 through 2011, I find that cities demand airline passengers in proportion to their population size, but when viewed separately, demand for business passengers as a function of city size is much lower than for leisure passengers. Moreover, I find that these patterns have remained relatively stable over the last two decades. The findings suggest that considering passenger type is important in evaluating the sustainability of air transport and the capacity of the air transport system to support cities' continued growth.

Claims about the strength of cities' global connections have become commonplace in the world cities literature. Although such claims are inherently comparative, authors often do not specify the reference. London is well connected compared to what? In this paper, I adapt the stochastic degree sequence model from network analysis as a tool to derive a frame of reference that can be used to inform and substantiate such claims. Beyond providing a formal statistical method for deciding when the claim that "X is well connected" is justified, it also addresses a number of other challenges in this literature, including more explicitly casting firms as key agents in world city formation, providing insight into when and where global firms might be expected to locate their branch offices, and helping identify cases that warrant more detailed investigation. To illustrate, I apply the method to data on cities and firms from 2013, examining the results at five different scales, from the individual city and firm to the entire world city network. I conclude by considering how this approach allows researchers to ask different kinds of questions about the nature of world city status.