Behavior Dynamics in Media-Sharing Social Networks

Behavior Dynamics in Media-Sharing Social Networks

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In large-scale media-sharing social networks, where millions of users create, share, link and reuse media content, there are clear challenges in protecting content security and intellectual property, and in designing scalable and reliable networks capable of handling high levels of traffic. This comprehensive resource demonstrates how game theory can be used to model user dynamics and optimize design of media-sharing networks. It reviews the fundamental methodologies used to model and analyze human behavior, using examples from real-world multimedia social networks. With a thorough investigation of the impact of human factors on multimedia system design, this accessible book shows how an understanding of human behavior can be used to improve system performance. Bringing together mathematical tools and engineering concepts with ideas from sociology and human behavior analysis, this one-stop guide will enable researchers to explore this emerging field further and ultimately design media-sharing systems with more efficient, secure and personalized more

Product details

  • Electronic book text | 350 pages
  • Cambridge University Press (Virtual Publishing)
  • Cambridge, United Kingdom
  • English
  • 110 b/w illus. 7 tables
  • 1139065297
  • 9781139065290

Table of contents

Preface; Part I. Introduction: 1. Introduction to media-sharing social networks; 2. Overview of multimedia fingerprinting; 3. Overview of mesh-pull peer-to-peer video streaming; 4. Game theory for social networks; Part II. Behavior Forensics in Media-Sharing Social Networks: 5. Equal-risk fairness in colluder social networks; 6. Leveraging side information in colluder social networks; 7. Risk-distortion analysis of multiuser collusion; Part III. Fairness and Cooperation Stimulation: 8. Game-theoretic modelling of colluder social networks; 9. Cooperation stimulation in peer-to-peer video streaming; 10. Optimal pricing for mobile video streaming; Part IV. Misbehaving User Identification: 11. Cheating behavior in colluder social networks; 12. Attack resistance in peer-to-peer video streaming; 13. Misbehavior detection in colluder social networks with different structures; 14. Structuring cooperation for hybrid peer-to-peer streaming; References; more

Review quote

'... the authors provide mathematical means for analysis of socially-enabled media sharing networks and their performance ... one may find ... inspiration in the book.' IEEE Communications Magazineshow more

About H. Vicky Zhao

H. Vicky Zhao is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Alberta. The recipient of the IEEE Signal Processing Society Young Author Best Paper Award 2008, she is an Associate Editor for the IEEE Signal Processing Letters and the Journal of Visual Communication and Image Representation. W. Sabrina Lin is a Research Associate in the Department of Electrical and Computer Engineering at the University of Maryland. She received the University of Maryland Future Faculty Fellowship in 2007. K. J. Ray Liu is a Distinguished Scholar-Teacher of the University of Maryland. He received the IEEE Signal Processing Society Technical Achievement Award in 2009, and was Editor-in-Chief of the IEEE Signal Processing Magazine and the founding Editor-in-Chief of the EURASIP Journal on Advances in Signal more

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