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Social Media Modeling and Computing [electronic resource] / edited by Steven C.H. Hoi, Jiebo Luo, Susanne Boll, Dong Xu, Rong Jin, Irwin King.

By: Contributor(s): Material type: TextTextPublisher: London : Springer London, 2011Description: XIII, 286 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780857294364
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.4 23
LOC classification:
  • Q337.5
  • TK7882.P3
Online resources:
Contents:
Quantifying Visual-Representativeness of Social Image Tags using Image Tag Clarity -- Tag-Based Social Image Search: Towards Relevant and Diverse Results -- Social Image Tag Ranking by Two-View Learning -- Combining Multi-modal Features for Social Media Analysis -- Multi-label Image Annotation by Structural Grouping Sparsity -- Mechanism Design for Incentivizing Social Media Contributions -- Efficient Access Control in Multimedia Social Networks -- Call Me Guru: User Categories and Large-Scale Behavior in YouTube -- Social Media Visual Analytics for Events -- Using Rich Social Media Information for Music Recommendation via Hypergraph Model -- Using Geotags to Derive Rich Tagclouds for Image Annotation -- Social Aspects of Photobooks: Improving Photobook Authoring from Large-Scale Multimedia Analysis.
In: Springer eBooksSummary: The emergence of user-centric multimedia applications on social networks has been instrumental in the creation of a new form of “social” media – created using highly accessible and scalable publishing technologies for sharing via the internet. This timely text/reference presents the latest advances in various aspects of social media modeling and social media computing research. Gathering together superb research from a range of established international conferences and workshops, the editors coherently organize and present each of the topics in relation to the basic principles and practices of social media modeling and computing. Individual chapters can be also be used as self-contained references on the material covered. Topics and features: Presents contributions from an international selection of preeminent experts in the field Discusses topics on social-media content analysis, including social-image tag analysis and ranking, tag-based social image search, analysis by combining multimodal features, and multi-label social-image annotation Examines social-media system design and analysis, covering mechanisms for incentivizing contributions, analysis of users and online behaviors in video sharing portals, and visual analytic tools for event analysis Investigates access control for privacy and security issues in social networks Describes emerging applications of social media, for music recommendation, automatic image annotation, and the analysis and improvement of photo-books This unique text is a must-read, must-use tool for software developers, researchers and graduate students working on multimedia, web search, data mining and machine learning, and related disciplines. High-level managers and professional engineers interested in emerging social media modeling and computing technologies will also find the book to be an invaluable reference. Dr. Steven C.H. Hoi and Dr. Dong Xu are both assistant professors in the School of Computer Engineering at Nanyang Technological University, Singapore. Dr. Jiebo Luo is a senior principal scientist with the Kodak Research Laboratories in Rochester, NY, USA. Dr. Susanne Boll is a professor in the Department of Computer Science at the University of Oldenburg, Germany. Dr. Rong Jin is an associate professor in the Department of Computer Science and Engineering at Michigan State University, East Lansing, MI, USA. Dr. Irwin King is a professor in the Department of Computer Science and Engineering at the Chinese University of Hong Kong, Shatin, Hong Kong.
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E-Book E-Book Central Library Available E-38282

Quantifying Visual-Representativeness of Social Image Tags using Image Tag Clarity -- Tag-Based Social Image Search: Towards Relevant and Diverse Results -- Social Image Tag Ranking by Two-View Learning -- Combining Multi-modal Features for Social Media Analysis -- Multi-label Image Annotation by Structural Grouping Sparsity -- Mechanism Design for Incentivizing Social Media Contributions -- Efficient Access Control in Multimedia Social Networks -- Call Me Guru: User Categories and Large-Scale Behavior in YouTube -- Social Media Visual Analytics for Events -- Using Rich Social Media Information for Music Recommendation via Hypergraph Model -- Using Geotags to Derive Rich Tagclouds for Image Annotation -- Social Aspects of Photobooks: Improving Photobook Authoring from Large-Scale Multimedia Analysis.

The emergence of user-centric multimedia applications on social networks has been instrumental in the creation of a new form of “social” media – created using highly accessible and scalable publishing technologies for sharing via the internet. This timely text/reference presents the latest advances in various aspects of social media modeling and social media computing research. Gathering together superb research from a range of established international conferences and workshops, the editors coherently organize and present each of the topics in relation to the basic principles and practices of social media modeling and computing. Individual chapters can be also be used as self-contained references on the material covered. Topics and features: Presents contributions from an international selection of preeminent experts in the field Discusses topics on social-media content analysis, including social-image tag analysis and ranking, tag-based social image search, analysis by combining multimodal features, and multi-label social-image annotation Examines social-media system design and analysis, covering mechanisms for incentivizing contributions, analysis of users and online behaviors in video sharing portals, and visual analytic tools for event analysis Investigates access control for privacy and security issues in social networks Describes emerging applications of social media, for music recommendation, automatic image annotation, and the analysis and improvement of photo-books This unique text is a must-read, must-use tool for software developers, researchers and graduate students working on multimedia, web search, data mining and machine learning, and related disciplines. High-level managers and professional engineers interested in emerging social media modeling and computing technologies will also find the book to be an invaluable reference. Dr. Steven C.H. Hoi and Dr. Dong Xu are both assistant professors in the School of Computer Engineering at Nanyang Technological University, Singapore. Dr. Jiebo Luo is a senior principal scientist with the Kodak Research Laboratories in Rochester, NY, USA. Dr. Susanne Boll is a professor in the Department of Computer Science at the University of Oldenburg, Germany. Dr. Rong Jin is an associate professor in the Department of Computer Science and Engineering at Michigan State University, East Lansing, MI, USA. Dr. Irwin King is a professor in the Department of Computer Science and Engineering at the Chinese University of Hong Kong, Shatin, Hong Kong.

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