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Computational Network Science
An Algorithmic Approach
1st Edition - September 23, 2014
Author: Henry Hexmoor
Language: English
Paperback ISBN:9780128008911
9 7 8 - 0 - 1 2 - 8 0 0 8 9 1 - 1
eBook ISBN:9780128011560
9 7 8 - 0 - 1 2 - 8 0 1 1 5 6 - 0
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 sc…Read more
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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
Network researchers and graduate students; professionals in computational disciplines; researchers in most scientific, social, and cross-disciplinary fields
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
No. of pages: 128
Language: English
Edition: 1
Published: September 23, 2014
Imprint: Morgan Kaufmann
Paperback ISBN: 9780128008911
eBook ISBN: 9780128011560
HH
Henry Hexmoor
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