Includes bibliographical references at the end of each chapters.

Online resource; title from PDF title page (ebrary, viewed October 9, 2014).

Cover; Title Page; Copyright Page; Table of contents; Preface; References; Chapter 1 -- Ubiquity of Networks; 1.1 -- Introduction; 1.2 -- Online social networking services; 1.3 -- Online bibliographic services; 1.4 -- Generic network models; 1.4.1 -- Random Networks; 1.4.2 -- Scale-Free Networks; 1.4.3 -- Trade-Off Model; 1.4.4 -- Game Theoretic Models; 1.5 -- Network model generators; 1.5.1 -- Kleinberg's Small-World Model; 1.5.2 -- Barab�asi and Albert's Scale-Free Network Generator; 1.5.3 -- Epstein and Wang's Power-Law Network Generator; 1.6 -- A real-world network; 1.7 -- Conclusions.

5.3 -- Markov chains5.4 -- Strategic network partnering using Markov decision processes; 5.5 -- Conclusion; References; Chapter 6 -- Diffusion and Contagion; 6.1 -- Population preference spread; 6.2 -- Percolation model; 6.3 -- Disease epidemic models; 6.4 -- Community detection; 6.4.1 -- Spectral Clustering; 6.4.2 -- Hierarchical Clustering; 6.4.3 -- Cascade Model; 6.4.4 -- Independent Contagion Model; 6.4.5 -- Node-Centric Community Detection; 6.5 -- Community correlation versus influence; 6.6 -- Conclusion; References; Chapter 7 -- Influence Diffusion and Contagion; 7.1 -- Stochastic model.

7.2 -- Social learning7.3 -- Social media influence; 7.3.1 -- Social Media: A Case for Facebook and Twitter; 7.3.2 -- Klout Score; 7.4 -- Conclusion; References; Chapter 8 -- Power in Exchange Networks; 8.1 Conclusion; References; Chapter 9 -- Economic Networks; 9.1 -- Network effects; 9.2 -- Conclusion; References; Chapter 10 -- Network Capital; 10.1 -- Social capital used for physical capital access; 10.1.1 -- Intermediaries; 10.1.2 -- A Basic Protocol for Resource Access Using Social Capital; 10.2 -- Conclusion; References; Chapter 11 -- Network Organizations; 11.1 Conclusion ; References.

Chapter 12 -- Emerging Trends12.1 -- Conclusion; References; Appendix.

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 disciplin.