The Complexity in the Study of Spatial Networks: an Epistemological Approach

Tsiotas, Dimitrios; Polyzos, Serafeim

doi:10.1007/s11067-017-9354-1

Cited by 34 publications

(30 citation statements)

References 96 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These measures were selected in the analysis from a broader set of network measures available in the literature (1,6,13), because they were the only ones having distinct statistical properties for any pair of the three network types BA, RL, and LL, and thus their overall view may give insights about what network topology is, in total (see ref. 10).…”

Section: Simulations and Analysismentioning

confidence: 99%

Detecting different topologies immanent in scale-free networks with the same degree distribution

Tsiotas

2019

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

The scale-free (SF) property is a major concept in complex networks, and it is based on the definition that an SF network has a degree distribution that follows a power-law (PL) pattern. This paper highlights that not all networks with a PL degree distribution arise through a Barabási−Albert (BA) preferential attachment growth process, a fact that, although evident from the literature, is often overlooked by many researchers. For this purpose, it is demonstrated, with simulations, that established measures of network topology do not suffice to distinguish between BA networks and other (random-like and latticelike) SF networks with the same degree distribution. Additionally, it is examined whether an existing self-similarity metric proposed for the definition of the SF property is also capable of distinguishing different SF topologies with the same degree distribution. To contribute to this discrimination, this paper introduces a spectral metric, which is shown to be more capable of distinguishing between different SF topologies with the same degree distribution, in comparison with the existing metrics.network science | Barabási−Albert networks | preferential attachment | pattern recognition | power-law degree distribution

show abstract

Section: Simulations and Analysismentioning

confidence: 99%

Detecting different topologies immanent in scale-free networks with the same degree distribution

Tsiotas

2019

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

show abstract

“…A useful starting point can be found in the idea that any socio-political aggregation that has an interest in common could, in principle, organize itself to promote policies that favor its interests. For this purpose, the concept of 'potential interest group' (Truman 1951) can be particularly useful. The idea is to identify what sociopolitical aggregations (based on division of labor) can be seen as potential stakeholders and what their interests may be, irrespective of whether they actually organize themselves to exert an influence on policy to pursue those interests.…”

Section: Structural Representations Of Socio-economic Systems: From Smentioning

confidence: 99%

Vulnerability, Resilience and ‘Systemic Interest’: a Connectivity Approach

Cardinale

2019

Netw Spat Econ

View full text Add to dashboard Cite

This paper analyzes the socioeconomic dimension of vulnerability and resilience from the viewpoint of connectivity. While no consensus has yet emerged on the definitions of vulnerability and resilience or on their relationship, it has been recognized that both have an important normative dimension, in that whether a system is considered vulnerable or resilient depends on the interests of the stakeholders involved. The paper proposes a dimension of resilience and vulnerability that is likely to be shared across a significant spectrum of stakeholders. To do so, the paper analyses connectivity within social-ecological systems from a BStructural Political Economy^viewpoint. A key concept in this regard is Bsystemic interest^, which is defined as the interest of stakeholders in keeping viable the system of connections within which they act. Systemic interest has desirable properties to conceptualize the normative dimension of vulnerability and resilience and leads to problematize their link with connectivity. In fact, it raises the question of what features of connectivity can be expected to lead to systemic interest, and how this impinges on vulnerability and resilience in different contexts. On the one hand, one might expect that a more interconnected system is more vulnerable to shocks, which propagate more easily throughout the system. On the other hand, such system might have a stronger systemic interest, so that a shock would trigger stakeholders' reaction to counteract its effects and avoid systemic consequences. The paper points to the institutional conditions that might make either outcome more likely in any given context.

show abstract

“…They shape travel behavior, location decisions, and the texture of the urban fabric (Jacobs 1995;Levinson and El-Geneidy 2009;Parthasarathi et al 2015). Accordingly, researchers have recently devoted much attention to street network patterns, performance, complexity, and configuration (Barthelemy et al 2013;Batty 2005a;Boeing 2018a;Buhl et al 2006;Chan et al 2011;Ducruet and Beauguitte 2014;Jiang et al 2014;Jiang and Claramunt 2004;Marshall 2004;Masucci et al 2013;Nilsson and Gil 2019;Tsiotas and Polyzos 2018;Wang 2015). In these spatial networks, entropy has deep theoretical connections with complexity (Batty 2005b;Batty et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Urban spatial order: street network orientation, configuration, and entropy

2019

View full text Add to dashboard Cite

Street networks may be planned according to clear organizing principles or they may evolve organically through accretion, but their configurations and orientations help define a city's spatial logic and order. Measures of entropy reveal a city's streets' order and disorder. Past studies have explored individual cases of orientation and entropy, but little is known about broader patterns and trends worldwide. This study examines street network orientation, configuration, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx. It measures the entropy of street bearings in weighted and unweighted network models, along with each city's typical street segment length, average circuity, average node degree, and the network's proportions of four-way intersections and dead-ends. It also develops a new indicator of orientation-order that quantifies how a city's street network follows the geometric ordering logic of a single grid. A cluster analysis is performed to explore similarities and differences among these study sites in multiple dimensions. Significant statistical relationships exist between city orientation-order and other indicators of spatial order, including street circuity and measures of connectedness. On average, US/Canadian study sites are far more grid-like than those elsewhere, exhibiting less entropy and circuity. These indicators, taken in concert, help reveal the extent and nuance of the grid. These methods demonstrate automatic, scalable, reproducible tools to empirically measure and visualize city spatial order, illustrating complex urban transportation system patterns and configurations around the world.

show abstract

The Complexity in the Study of Spatial Networks: an Epistemological Approach

Cited by 34 publications

References 96 publications

Detecting different topologies immanent in scale-free networks with the same degree distribution

Detecting different topologies immanent in scale-free networks with the same degree distribution

Vulnerability, Resilience and ‘Systemic Interest’: a Connectivity Approach

Urban spatial order: street network orientation, configuration, and entropy

Contact Info

Product

Resources

About