Computational Network Science

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  • Publisher : Morgan Kaufmann
  • Release : 23 September 2014
  • ISBN : 9780128011560
  • Page : 128 pages
  • Rating : 4.5/5 from 103 voters

Computational Network Science Book PDF summary

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline. Computational Network Science seeks to unify the methods used to analyze these diverse fields. This book provides an introduction to the field of Network Science and provides the groundwork for a computational, algorithm-based approach to network and system analysis in a new and important way. This new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research. Demystifies media hype regarding Network Science and serves as a fast-paced introduction to state-of-the-art concepts and systems related to network science Comprehensive coverage of Network Science algorithms, methodologies, and common problems Includes references to formative and updated developments in the field Coverage spans mathematical sociology, economics, political science, and biological networks

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Computational Network Science

Computational Network Science
  • Author : Henry Hexmoor
  • Publisher : Morgan Kaufmann
  • Release Date : 2014-09-23
  • ISBN : 9780128011560
DOWNLOAD BOOKComputational Network Science

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has

Computational Network Analysis with R

Computational Network Analysis with R
  • Author : Matthias Dehmer,Yongtang Shi,Frank Emmert-Streib
  • Publisher : John Wiley & Sons
  • Release Date : 2016-12-12
  • ISBN : 9783527339587
DOWNLOAD BOOKComputational Network Analysis with R

This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference

Network Science

Network Science
  • Author : Ernesto Estrada,Maria Fox,Desmond J. Higham,Gian-Luca Oppo
  • Publisher : Springer Science & Business Media
  • Release Date : 2010-08-24
  • ISBN : 9781849963961
DOWNLOAD BOOKNetwork Science

Network Science is the emerging field concerned with the study of large, realistic networks. This interdisciplinary endeavor, focusing on the patterns of interactions that arise between individual components of natural and engineered systems, has been applied to data sets from activities as diverse as high-throughput biological experiments, online trading information, smart-meter utility supplies, and pervasive telecommunications and surveillance technologies. This unique text/reference provides a fascinating insight into the state of the art in network science, highlighting the commonality across

Computational Network Theory

Computational Network Theory
  • Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl
  • Publisher : John Wiley & Sons
  • Release Date : 2015-11-02
  • ISBN : 9783527337248
DOWNLOAD BOOKComputational Network Theory

This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are important tools to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and

A First Course in Network Science

A First Course in Network Science
  • Author : Filippo Menczer,Santo Fortunato,Clayton A. Davis
  • Publisher : Cambridge University Press
  • Release Date : 2020-01-31
  • ISBN : 9781108471138
DOWNLOAD BOOKA First Course in Network Science

A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.

Network Science

Network Science
  • Author : Albert-László Barabási
  • Publisher : Cambridge University Press
  • Release Date : 2016-07-21
  • ISBN : 9781107076266
DOWNLOAD BOOKNetwork Science

Illustrated throughout in full colour, this pioneering text is the only book you need for an introduction to network science.

Analyzing Network Data in Biology and Medicine

Analyzing Network Data in Biology and Medicine
  • Author : Nata a Pr ulj,Nataša Pržulj
  • Publisher : Cambridge University Press
  • Release Date : 2019-03-28
  • ISBN : 9781108432238
DOWNLOAD BOOKAnalyzing Network Data in Biology and Medicine

Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

Mining Complex Networks

Mining Complex Networks
  • Author : Bogumil Kaminski,Pawel Prałat,Francois Theberge
  • Publisher : CRC Press
  • Release Date : 2021-12-14
  • ISBN : 9781000515909
DOWNLOAD BOOKMining Complex Networks

This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision-making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks aim to understand the principles governing the organization and the behavior

Computational Network Science

Computational Network Science
  • Author : Henry Hexmoor
  • Publisher : Morgan Kaufmann
  • Release Date : 2014-09-29
  • ISBN : 0128008911
DOWNLOAD BOOKComputational Network Science

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has

Computational Approaches to the Network Science of Teams

Computational Approaches to the Network Science of Teams
  • Author : Liangyue Li,Hanghang Tong
  • Publisher : Cambridge University Press
  • Release Date : 2020-12-03
  • ISBN : 9781108498548
DOWNLOAD BOOKComputational Approaches to the Network Science of Teams

Surveys recent models and algorithms characterizing, predicting, optimizing, and explaining team performance in a variety of settings.

Introduction to Computational Social Science

Introduction to Computational Social Science
  • Author : Claudio Cioffi-Revilla
  • Publisher : Springer
  • Release Date : 2017-06-29
  • ISBN : 9783319501314
DOWNLOAD BOOKIntroduction to Computational Social Science

This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains

Computational Network Theory

Computational Network Theory
  • Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl
  • Publisher : John Wiley & Sons
  • Release Date : 2015-05-04
  • ISBN : 9783527691548
DOWNLOAD BOOKComputational Network Theory

This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and

Mining Lurkers in Online Social Networks

Mining Lurkers in Online Social Networks
  • Author : Andrea Tagarelli,Roberto Interdonato
  • Publisher : Springer
  • Release Date : 2018-11-09
  • ISBN : 9783030002299
DOWNLOAD BOOKMining Lurkers in Online Social Networks

This SpringerBrief brings order to the wealth of research studies that contribute to shape our understanding of on-line social networks (OSNs) lurking phenomena. This brief also drives the development of computational approaches that can be effectively applied to answer questions related to lurking behaviors, as well as to the engagement of lurkers in OSNs. All large-scale online social networks (OSNs) are characterized by a participation inequality principle, i.e., the crowd of an OSN does not actively contribute, rather it

Network Models for Data Science

Network Models for Data Science
  • Author : Alan Julian Izenman
  • Publisher : Cambridge University Press
  • Release Date : 2022-11-30
  • ISBN : 1108835767
DOWNLOAD BOOKNetwork Models for Data Science

This text on the theory and applications of network science is aimed at beginning graduate students in statistics, data science, computer science, machine learning, and mathematics, as well as advanced students in business, computational biology, physics, social science, and engineering working with large, complex relational data sets. It provides an exciting array of analysis tools, including probability models, graph theory, and computational algorithms, exposing students to ways of thinking about types of data that are different from typical statistical data.

Network Science in Cognitive Psychology

Network Science in Cognitive Psychology
  • Author : Michael S. Vitevitch
  • Publisher : Routledge
  • Release Date : 2019-11-26
  • ISBN : 9781000740684
DOWNLOAD BOOKNetwork Science in Cognitive Psychology

This volume provides an integrative review of the emerging and increasing use of network science techniques in cognitive psychology, first developed in mathematics, computer science, sociology, and physics. The first resource on network science for cognitive psychologists in a growing international market, Vitevitch and a team of expert contributors provide a comprehensive and accessible overview of this cutting-edge topic. This innovative guide draws on the three traditional pillars of cognitive psychological research–experimental, computational, and neuroscientific–and incorporates the latest