Prediction and Inference from Social Networks and Social Media
Editors: Kawash, Jalal, Agarwal, Nitin, Özyer, Tansel (Eds.)
Free Preview- Demonstrates new mining techniques and applications for social networking within the fields of prediction and inference
- Proposes a wide variety of social network research topics
- Covers a wide variety of case studies and state-of-the-art analysis tools for Facebook and Twitter
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- About this book
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This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field.
- Table of contents (9 chapters)
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Having Fun?: Personalized Activity-Based Mood Prediction in Social Media
Pages 1-18
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Automatic Medical Image Multilingual Indexation Through a Medical Social Network
Pages 19-49
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The Significant Effect of Overlapping Community Structures in Signed Social Networks
Pages 51-84
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Extracting Relations Between Symptoms by Age-Frame Based Link Prediction
Pages 85-95
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Link Prediction by Network Analysis
Pages 97-114
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Table of contents (9 chapters)
- Download Preface 1 PDF (58.6 KB)
- Download Sample pages 1 PDF (6 MB)
- Download Table of contents PDF (34 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Prediction and Inference from Social Networks and Social Media
- Editors
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- Jalal Kawash
- Nitin Agarwal
- Tansel Özyer
- Series Title
- Lecture Notes in Social Networks
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-51049-1
- DOI
- 10.1007/978-3-319-51049-1
- Hardcover ISBN
- 978-3-319-51048-4
- Softcover ISBN
- 978-3-319-84553-1
- Series ISSN
- 2190-5428
- Edition Number
- 1
- Number of Pages
- IX, 225
- Number of Illustrations
- 28 b/w illustrations, 54 illustrations in colour
- Topics
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