000			02946nam a2200253Ia 4500
003			NULRC
005			20250520102820.0
008			250520s9999 xx 000 0 und d
020			_a9780198726463
040			_cNULRC
050			_aQ 295 .E88 2015
100			_aEstrada, Ernesto _eauthor
245		2	_aA first course in network theory / _cErnesto Estrada and Philip A. Knight.
250			_aFirst edition
260			_aOxford, United Kingdom : _bOxford University Press, _cc2015
300			_axiv, 288 pages ; _c25 cm.
365			_bUSD53.96
504			_aIncludes bibliographical references and index.
505			_aIntroduction to network theory -- General concepts in network theory -- How to prove it -- Data analysis and manipulation -- Algebraic concepts in network theory -- Spectra of adjacency matrices -- The network Laplacian -- Classical physics analogies -- Degree distributions -- Clustering coefficients of networks -- Random models of networks -- Matrix functions -- Fragment-based measures -- Classical node centrality -- Spectral node centrality -- Quantum physics analogies -- Global properties of networks I -- Global properties of networks II -- Communicability in networks -- Statistical physics analogies -- Communities in networks.
520			_aThe study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and sociology. This book promotes the diverse nature of the study of complex networks by balancing the needs of students from very different backgrounds. It references the most commonly used concepts in network theory, provides examples of their applications in solving practical problems, and clear indications on how to analyse their results. In the first part of the book, students and researchers will discover the quantitative and analytical tools necessary to work with complex networks, including the most basic concepts in network and graph theory, linear and matrix algebra, as well as the physical concepts most frequently used for studying networks. They will also find instruction on some key skills such as how to proof analytic results and how to manipulate empirical network data. The bulk of the text is focused on instructing readers on the most useful tools for modern practitioners of network theory. These include degree distributions, random networks, network fragments, centrality measures, clusters and communities, communicability, and local and global properties of networks. The combination of theory, example and method that are presented in this text, should ready the student to conduct their own analysis of networks with confidence and allow teachers to select appropriate examples and problems to teach this subject in the classroom.
650			_aSYSTEM ANALYSIS -- TEXTBOOKS
700			_aKnight, Philip A. _eco-author
942			_2lcc _cBK
999			_c16036 _d16036