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Emergent patterns in complex networks

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Klaise, Janis (2017) Emergent patterns in complex networks. PhD thesis, University of Warwick.

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Official URL: http://webcat.warwick.ac.uk/record=b3171626~S1

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Abstract

Complex interacting systems permeate the modern world. Many diverse natural, social and human made systems—ranging from food webs to human contact networks, to the Internet—can be studied in the context of network science. This thesis is a compendium of research in applied network science, investigating structural and dynamical patterns behind the formation of networks and processes supported on them.
Trophic food webs—networks of who eats whom in an ecosystem—have fascinated network scientists since data from field observations of the gut content of species first became available. The empirical patterns in food webs reveal a rich hierarchy of feeding patterns. We study how global structure of food webs relates to species immediate diet over a range of 46 different ecosystems. Our finding suggest that food webs fall broadly into two different families based on the extent of species tendency towards omnivory.
Drawing inspiration from food webs, we investigate how trophic networks support spreading processes on them. We find that the interplay of dynamics and network structure determines the extent and duration of contagion. We uncover two distinct modes of operation—short-lived outbreaks with high incidence and endemic infections. These results could be important for understanding spreading phenomena such as epidemics, rumours, shocks to ecosystems and neuronal avalanches.
Finally, we study the emergence of structural order in random network models. Random networks serve as null models to empirical networks to help uncover significant non-random patterns but are also interesting to study in their own right. We study the effect of triadic ties in delaying the formation of extensive giant components— connected components taking over the majority of the network. Our results show that, depending on the network formation process, order in the form of a giant component can emerge even with a significant number of triadic ties

Item Type: Thesis (PhD)
Subjects: Q Science > QA Mathematics
Library of Congress Subject Headings (LCSH): Graph theory, System analysis -- Mathematical models, System theory -- Mathematical models
Official Date: December 2017
Dates:
DateEvent
December 2017Submitted
Institution: University of Warwick
Theses Department: Centre for Complexity Science
Thesis Type: PhD
Publication Status: Unpublished
Supervisor(s)/Advisor: Johnson, Samuel
Extent: xii, 112 leaves : illustrations.
Language: eng

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