04289nam 22007332 450 991079007410332120151005020622.01-107-21486-61-283-11248-597866131124841-139-07563-21-139-08018-01-139-07789-91-139-06987-X0-511-97336-51-139-08246-9(CKB)2670000000088893(EBL)691901(OCoLC)726734782(SSID)ssj0000521101(PQKBManifestationID)11325835(PQKBTitleCode)TC0000521101(PQKBWorkID)10514682(PQKB)10472590(UkCbUP)CR9780511973369(Au-PeEL)EBL691901(CaPaEBR)ebr10470690(CaONFJC)MIL311248(MiAaPQ)EBC691901(PPN)261364375(EXLCZ)99267000000008889320101011d2011|||| uy| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierBehavior dynamics in media-sharing social networks /H. Vicky Zhao, W. Sabrina Lin, K. J. Ray Liu[electronic resource]Cambridge :Cambridge University Press,2011.1 online resource (xii, 337 pages) digital, PDF file(s)Title from publisher's bibliographic system (viewed on 05 Oct 2015).1-139-06529-7 0-521-19727-9 Includes bibliographical references and index.Machine generated contents note: 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; Index.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 services.Social networksConsumer behaviorHuman behaviorGame theorySocial networks.Consumer behavior.Human behavior.Game theory.302.30285/675Zhao H. Vicky1976-1493027Lin W. Sabrina1981-Liu K. J. Ray1961-UkCbUPUkCbUPBOOK9910790074103321Behavior dynamics in media-sharing social networks3715840UNINA