Small-world characteristics in geographic, epidemic, and virtual spaces : a comparative study
Year: 2007
Type: dissertation
Abstract: This dissertation focuses on a comparative study of small-world characteristics in\ngeographical, epidemic, and virtual spaces. Small-world network is the major\ncomponent of the “new science of networks” that emerged recently in research related to\ncomplex networks. It has shown a great potential to model the complex networks\nencountered in geographical studies. This dissertation, in an attempt to understand the\nemergence of small-world phenomenon in spatial networks, has investigated the smallworld\nproperties in aforementioned three spaces.\nSpecifically, this dissertation has studied roadway transportation networks at national,\nmetropolitan, and intra-city scales via network autocorrelation methods to investigate the\ndistance effect on the emergence of small-world properties. This dissertation also\ninvestigated the effect of small-world network properties on the epidemic diffusion and\ndifferent control strategies through agent-based simulation on social networks. The ASLevel\nInternet in the contiguous U.S. has been studied in its relation between local and\nglobal connections, and its correspondence with small-world characteristics. Through theoretical simulations and empirical studies on spatial networks, this\ndissertation has contributed to network science with a new method – network\nautocorrelation, and better understanding from the perspective of the relation between\nlocal and global connections and the distance effect in networks. A small-world\nphenomenon results from the interplay between the dynamics occurring on networks and\nthe structure of networks; when the influencing distance of the dynamics reaches to the\nthreshold of the network, the network will logically emerge as a small-world network.\nWith the aid of numerical simulation a small-world network has a large number of local\nconnections and a small number of global links. It is also found that the epidemics will\ntake shorter time period to reach largest size on a small-world network and only\nparticular control strategy, such as targeted control strategy, will be effective on smallworld\nnetworks.\nThis dissertation bridges the gap between new science of networks and the network\nstudy in geography. It potentially contributes to GIScience with new modeling strategy\nfor representing, analyzing, and modeling complexity in hazards prevention, landscape\necology, and sustainability science from a network-centric perspective.
Author: Zengwang Xu
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2295769159