000			03222cam a22004815i 4500
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003			BD-DhUL
005			20220920121034.0
006			m |o d |
007			cr |||||||||||
008			180825s2018 sz a||| |b |||1 0|eng
010			_a 2019759295
020			_a9783319967462 (hbk)
024	7		_a10.1007/978-3-319-96746-2 _2doi
035			_a(DE-He213)978-3-319-96746-2
040			_aDLC _beng _epn _erda _cDLC _dBD-DhUL
072		7	_aCOM075000 _2bisacsh
072		7	_aUKN _2bicssc
072		7	_aUKN _2thema
082			_a004.6 _bMKP
100	1		_aM., Krishna Raj P.
245	1	0	_aPractical Social Network Analysis with Python / _cby Krishna Raj P. M., Ankith Mohan, K.G. Srinivasa.
260			_aCham : _bSpringer, _c2018.
300			_axxxi, 329 p. : _bill. (some col.) ; _c24 cm.
365			_aEuro _b139.99
490	0		_aComputer communications and networks.
504			_aIncludes bibliographical references and index.
520			_aThis book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
588			_aDescription based on publisher-supplied MARC data.
650		0	_aComputer communication systems.
650		0	_aPython (Computer program language).
650	1	4	_aComputer Communication Networks. _0https://scigraph.springernature.com/ontologies/product-market-codes/I13022
650	2	4	_aPython. _0https://scigraph.springernature.com/ontologies/product-market-codes/I29080
700	1		_aMohan, Ankith. _ejt. aut.
700	1		_aSrinivasa, K.G. _ejt. aut.
776	0	8	_iPrint version: _tPractical social network analysis with Python. _z9783319967455 _w(DLC) 2018949639
776	0	8	_iPrinted edition: _z9783030072414
776	0	8	_iPrinted edition: _z9783319967455
776	0	8	_iPrinted edition: _z9783319967479
830		0	_aComputer Communications and Networks, _x1617-7975
906			_a0 _bibc _corigres _du _encip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c257059 _d257059