Evolution, growth and modeling of complex networks = 복잡계 네트워크의 진화와 성장 및 모델링

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Networked systems are ubiquitous in real world. And many complex systems in nature and society can be described in terms of complex network. To characterize topological structure and understand underlying principles that drive network evolution is a key issue in many fields including statistical physics. In this dissertation, we study evolution, growth and modeling of complex network. We analyze the structure and evolution of online social relationships by examining the temporal records of a bulletin board system (BBS) in a university. The nodes are user students. An edges is assigned to each dialogue between two students and it is defined as the appearance of the BBS ID of a student in the from- and to-field in each message. This yields a weighted network between the communicating students with an unambiguous group association of individuals. In contrast to a typical community network, where intracommunities (intercommunities) are strongly (weakly) tied, the BBS network contains hubs members who participate in many boards simultaneously but are strong tied, that is, they have a large degree and betweenness centrality and provide communication channels between communities. On the the other hand, intracommunities are rather homogeneously and weakly connected. Then we collect more temporal records of several online bulletin board systems and a movie actor network. We measure the growth rates of degree and strength of each vertex and weight of each edge within the framework of preferential attachment (PA).We also measure the probability of creating new edges between unconnected pairs of vertices. Next, based on the measured rates, linear and nonlinear growth models are constructed. We find that the dynamics of creating new edges and adding weight to existing edges in nonlocal manner is essential to reproduce the nonlinear degree-strength relationship. We also find that the degree-driven PA rule is more appropriate to real systems rather than the strength-driven o...
Advisors
Jeong, Ha-woongresearcher정하웅researcher
Description
한국과학기술원 : 물리학과,
Publisher
한국과학기술원
Issue Date
2009
Identifier
309034/325007  / 020045154
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 물리학과, 2009.2, [ ix, 72 p. ]

Keywords

Complex network; Complex systems; evolution of networks; network model; 복잡계; 복잡계 네트워크; 네트워크 모델

URI
http://hdl.handle.net/10203/47617
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=309034&flag=dissertation
Appears in Collection
PH-Theses_Ph.D.(박사논문)
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