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Social Media Modeling and Computing

Overview of attention for book
Cover of 'Social Media Modeling and Computing'

Table of Contents

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    Book Overview
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    Chapter 1 Quantifying Visual-Representativeness of Social Image Tags Using Image Tag Clarity
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    Chapter 2 Tag-Based Social Image Search: Toward Relevant and Diverse Results
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    Chapter 3 Social Image Tag Ranking by Two-View Learning
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    Chapter 4 Combining Multi-modal Features for Social Media Analysis
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    Chapter 5 Multi-label Image Annotation by Structural Grouping Sparsity
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    Chapter 6 Mechanism Design for Incentivizing Social Media Contributions
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    Chapter 7 Efficient Access Control in Multimedia Social Networks
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    Chapter 8 Call Me Guru: User Categories and Large-Scale Behavior in YouTube
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    Chapter 9 Social Media Visual Analytics for Events
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    Chapter 10 Using Rich Social Media Information for Music Recommendation via Hypergraph Model
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    Chapter 11 Using Geotags to Derive Rich Tag-Clouds for Image Annotation
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    Chapter 12 Social Aspects of Photobooks: Improving Photobook Authoring from Large-Scale Multimedia Analysis
Attention for Chapter 4: Combining Multi-modal Features for Social Media Analysis
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Citations

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Readers on

mendeley
11 Mendeley
Summary Dimensions citations
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Chapter title
Combining Multi-modal Features for Social Media Analysis
Chapter number 4
Book title
Social Media Modeling and Computing
Published in
ADS, January 2011
DOI 10.1007/978-0-85729-436-4_4
Book ISBNs
978-0-85729-435-7, 978-0-85729-436-4
Authors

Spiros Nikolopoulos, Eirini Giannakidou, Ioannis Kompatsiaris, Ioannis Patras, Athena Vakali

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 27%
Student > Ph. D. Student 2 18%
Professor 1 9%
Other 1 9%
Student > Master 1 9%
Other 1 9%
Unknown 2 18%
Readers by discipline Count As %
Computer Science 6 55%
Social Sciences 2 18%
Arts and Humanities 1 9%
Unknown 2 18%

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