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007			cr nn 008mamaa
008			220601s2012 sz | s |||| 0|eng d
020			_a9783031019005
024	7		_a10.1007/978-3-031-01900-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2012 EB
100	1		_aTang, Lei, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686198 _d1982-
245	1	0	_aPrivacy in Social Networks _cby Lei Tang, Huan Liu
250			_a1st edition 2012
264		1	_aCham _bSpringer International Publishing _c2012
300			_a1 recurso en línea (X, 96 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Data Mining and Knowledge Discovery _x2151-0075
505	0		_aSocial Media and Social Computing -- Nodes, Ties, and Influence -- Community Detection and Evaluation -- Communities in Heterogeneous Networks -- Social Media Mining.
520			_aThe past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of \emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information. Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media Mining.
988			_aSynthesis Collection of Technology_2012
650		7	_2embne _9686197 _aMedios sociales
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9431622 _aRedes sociales en Internet
700	1		_aLiu, Huan, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _949086 _d1958-
776	0	8	_iPrinted edition: _z9783031007729
776	0	8	_iPrinted edition: _z9783031030284
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01900-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _esc _zSI