Computational Network Science - 1st Edition - ISBN: 9780128008911, 9780128011560

Computational Network Science

1st Edition

An Algorithmic Approach

Authors: Henry Hexmoor
eBook ISBN: 9780128011560
Paperback ISBN: 9780128008911
Imprint: Morgan Kaufmann
Published Date: 29th September 2014
Page Count: 128
Tax/VAT will be calculated at check-out Price includes VAT (GST)
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
29.95
20.96
20.96
20.96
20.96
20.96
23.96
23.96
21.95
15.37
15.37
15.37
15.37
15.37
17.56
17.56
27.95
19.57
19.57
19.57
19.57
19.57
22.36
22.36
Unavailable
Price includes VAT (GST)
× DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Table of Contents

  • Preface
  • Chapter 1: Ubiquity of Networks
    • Abstract
    • 1.1. Introduction
    • 1.2. Online social networking services
    • 1.3. Online bibliographic services
    • 1.4. Generic network models
    • 1.5. Network model generators
    • 1.6. A real-world network
    • 1.7. Conclusions
  • Chapter 2: Network Analysis
    • Abstract
    • 2.1. Conclusions and future work
  • Chapter 3: Network Games
    • Abstract
    • 3.1. Game theory introduction
    • 3.2. Congestion games and resource pricing
    • 3.3. Cooperation in network synthesis game
    • 3.4. Bayesian games
    • 3.5. Applications
    • 3.6. Conclusion
  • Chapter 4: Balance Theory
    • Abstract
    • 4.1. Conclusion
  • Chapter 5: Network Dynamics
    • Abstract
    • 5.1. Evolutionary and volatile network dynamics
    • 5.2. Time graphs
    • 5.3. Markov chains
    • 5.4. Strategic network partnering using Markov decision processes
    • 5.5. Conclusion
  • Chapter 6: Diffusion and Contagion
    • Abstract
    • 6.1. Population preference spread
    • 6.2. Percolation model
    • 6.3. Disease epidemic models
    • 6.4. Community detection
    • 6.5. Community correlation versus influence
    • 6.6. Conclusion
  • Chapter 7: Influence Diffusion and Contagion
    • Abstract
    • 7.1. Stochastic model
    • 7.2. Social learning
    • 7.3. Social media influence
    • 7.4. Conclusion
  • Chapter 8: Power in Exchange Networks
    • Abstract
    • 8.1. Conclusion
  • Chapter 9: Economic Networks
    • Abstract
    • 9.1. Network effects
    • 9.2. Conclusion
  • Chapter 10: Network Capital
    • Abstract
    • 10.1. Social capital used for physical capital access
    • 10.2. Conclusion
  • Chapter 11: Network Organizations
    • Abstract
    • 11.1. Conclusion
  • Chapter 12: Emerging Trends
    • Abstract
    • 12.1. Conclusion
  • Appendix

Description

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.

Key Features

  • 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

Readership

Network researchers and graduate students; professionals in computational disciplines; researchers in most scientific, social, and cross-disciplinary fields


Details

No. of pages:
128
Language:
English
Copyright:
© Morgan Kaufmann 2015
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9780128011560
Paperback ISBN:
9780128008911

About the Authors

Henry Hexmoor Author

Henry Hexmoor, received an M.S. from Georgia Tech and a Ph.D. in Computer Science from the State University of New York, Buffalo in 1996. He is a long-time IEEE senior member and has taught at the University of North Carolina and the University of Arkansas. Currently, he is an associate professor with the Computer Science department at Southern Illinois University in Carbondale, IL. He has published widely in the fields of artificial intelligence and multiagent systems. His research interests include multiagent systems, artificial intelligence, cognitive science, mobile robotics, and predictive models for transportation systems.

Affiliations and Expertise

Associate Professor, Computer Science Department, Southern Illinois University, Carbondale, Illinois