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008			220331s2022 sz | s |||| 0|eng d
020			_a9783030757182
024	7		_a10.1007/978-3-030-75718-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.I52 _b2022 EB
100	1		_aDe Domenico, M. _q(Manlio), _d1984- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685397
245	1	0	_aMultilayer Networks: Analysis and Visualization : _bIntroduction to muxViz with R _cby Manlio De Domenico
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (XXXI, 105 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
505	0		_aPart 1. Multilayer Network Science: Analysis and Visualization -- 1. Introduction -- 2. Multilayer Networks: Overview -- 3. Multilayer Analysis: Fundamentals and Micro-scale -- 4. Multilayer Versatility and Triads -- 5. Multilayer Organization: Meso-scale -- 6. Other Multilayer Analyses based on Dynamical Processes -- 7. Visualizing Multilayer Networks and Data -- Part 2. Appendices -- A. Installing and Using muxViz.
520			_aThe adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the analysis and visualization of multilayer networks. Multilayer Networks: Analysis and Visualization provides a guided introduction to one of the most complete computational frameworks, named muxViz, with introductory information about the underlying theoretical aspects and a focus on the analytical side. Dozens of analytical scripts and examples to use the muxViz library in practice, by means of the Graphical User Interface or by means of the R scripting language, are provided. In addition to researchers in the field of network science, as well as practitioners interested in network visualization and analysis, this book will appeal to researchers without strong technical or computer science background who want to learn how to use muxViz software, such as researchers from humanities, social science and biology: audiences which are targeted by case studies included in the book. Other interdisciplinary audiences include computer science, physics, neuroscience, genetics, urban transport and engineering, digital humanities, social and computational social science. Readers will learn how to use, in a very practical way (i.e., without focusing on theoretical aspects), the algorithms developed by the community and implemented in the free and open-source software muxViz. The data used in the book is available on a dedicated (open and free) site.
988			_aSpringer_Computer_2022
650		7	_2embne _9164496 _aR (Lenguaje de programación)
650		7	_2embne _9141354 _aRedes informáticas
650		7	_2embne _9145622 _aSistemas de visualización de información
776	0	8	_iPrinted edition: _z9783030757175
776	0	8	_iPrinted edition: _z9783030757199
776	0	8	_iPrinted edition: _z9783030757205
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-75718-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b11/2022 _dz _esc _zSI