This dissertation focuses on a comparative study of small-world characteristics in
geographical, epidemic, and virtual spaces. Small-world network is the major
component of the âÂÂnew science of networksâ that emerged recently in research related to
complex networks. It has shown a great potential to model the complex networks
encountered in geographical studies. This dissertation, in an attempt to understand the
emergence of small-world phenomenon in spatial networks, has investigated the smallworld
properties in aforementioned three spaces.
Specifically, this dissertation has studied roadway transportation networks at national,
metropolitan, and intra-city scales via network autocorrelation methods to investigate the
distance effect on the emergence of small-world properties. This dissertation also
investigated the effect of small-world network properties on the epidemic diffusion and
different control strategies through agent-based simulation on social networks. The ASLevel
Internet in the contiguous U.S. has been studied in its relation between local and
global connections, and its correspondence with small-world characteristics. Through theoretical simulations and empirical studies on spatial networks, this
dissertation has contributed to network science with a new method â network
autocorrelation, and better understanding from the perspective of the relation between
local and global connections and the distance effect in networks. A small-world
phenomenon results from the interplay between the dynamics occurring on networks and
the structure of networks; when the influencing distance of the dynamics reaches to the
threshold of the network, the network will logically emerge as a small-world network.
With the aid of numerical simulation a small-world network has a large number of local
connections and a small number of global links. It is also found that the epidemics will
take shorter time period to reach largest size on a small-world network and only
particular control strategy, such as targeted control strategy, will be effective on smallworld
networks.
This dissertation bridges the gap between new science of networks and the network
study in geography. It potentially contributes to GIScience with new modeling strategy
for representing, analyzing, and modeling complexity in hazards prevention, landscape
ecology, and sustainability science from a network-centric perspective.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/5768 |
| Date | 17 September 2007 |
| Creators | Xu, Zengwang |
| Contributors | Sui, Daniel Z. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 1765056 bytes, electronic, application/pdf, born digital |
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