Spectral analysis of community structure in complex networks: a case study of book-borrowing networks

碩士 === 國立東華大學 === 物理學系 === 100 === In this study, we use book-borrowing records of National Dong-Hua university library between January 2009 to June 2012 to build a real social network which contains 13,241 nodes, i.e. readers. The degree distribution of this book-borrowing network is a exponent...

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Main Authors: Cing-De Gong, 龔清德
Other Authors: Chi-Ning Chen
Format: Others
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/3w93p7
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spelling ndltd-TW-100NDHU51980182018-04-29T04:16:33Z http://ndltd.ncl.edu.tw/handle/3w93p7 Spectral analysis of community structure in complex networks: a case study of book-borrowing networks 複雜網路之社群結構的頻譜分析:以圖書借閱網路為例 Cing-De Gong 龔清德 碩士 國立東華大學 物理學系 100 In this study, we use book-borrowing records of National Dong-Hua university library between January 2009 to June 2012 to build a real social network which contains 13,241 nodes, i.e. readers. The degree distribution of this book-borrowing network is a exponential decay function. Its short average path length(1.93) and high clustering coefficient(0.34) indicate the small-world feature. We go further to pick up two to three departments to build a small detailed book-borrowing network. Based on the number of the same books borrowed, we construct a similarity matrix to represent the relationship between nodes. By diagonalizing and analysing its eigenvalues and eigenvectors, we may probe the community structure in the book-borrowing network. Chi-Ning Chen 陳企寧 2012 學位論文 ; thesis 45
collection NDLTD
format Others
sources NDLTD
description 碩士 === 國立東華大學 === 物理學系 === 100 === In this study, we use book-borrowing records of National Dong-Hua university library between January 2009 to June 2012 to build a real social network which contains 13,241 nodes, i.e. readers. The degree distribution of this book-borrowing network is a exponential decay function. Its short average path length(1.93) and high clustering coefficient(0.34) indicate the small-world feature. We go further to pick up two to three departments to build a small detailed book-borrowing network. Based on the number of the same books borrowed, we construct a similarity matrix to represent the relationship between nodes. By diagonalizing and analysing its eigenvalues and eigenvectors, we may probe the community structure in the book-borrowing network.
author2 Chi-Ning Chen
author_facet Chi-Ning Chen
Cing-De Gong
龔清德
author Cing-De Gong
龔清德
spellingShingle Cing-De Gong
龔清德
Spectral analysis of community structure in complex networks: a case study of book-borrowing networks
author_sort Cing-De Gong
title Spectral analysis of community structure in complex networks: a case study of book-borrowing networks
title_short Spectral analysis of community structure in complex networks: a case study of book-borrowing networks
title_full Spectral analysis of community structure in complex networks: a case study of book-borrowing networks
title_fullStr Spectral analysis of community structure in complex networks: a case study of book-borrowing networks
title_full_unstemmed Spectral analysis of community structure in complex networks: a case study of book-borrowing networks
title_sort spectral analysis of community structure in complex networks: a case study of book-borrowing networks
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/3w93p7
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