Overview

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.

Full Product Details

Author:   Jalal Kawash ,  Nitin Agarwal ,  Tansel Özyer
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   Softcover reprint of the original 1st ed. 2017
Weight:   0.454kg
ISBN:  

9783319845531

ISBN 10:   3319845535
Pages:   225
Publication Date:   18 July 2018
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Chapter1. Having Fun?: Personalized Activity-based Mood Prediction in Social Media.- Chapter2. Automatic Medical Image Multilingual Indexation through a Medical Social Network.- Chapter3. The Significant Effect of Overlapping Community Structures in Signed Social Networks.- Chapter4. Extracting Relations Between Symptoms by Age-Frame Based Link Prediction.- Chapter5. Link Prediction by Network Analysis.- Chapter6. Structure-Based Features for Predicting the Quality of Articles in Wikipedia.- Chapter7. Predicting Collective Action from Micro-Blog Data.- Chapter8. Discovery of Structural and Temporal Patterns in MOOC Discussion Forums.- Chapter9. Diffusion Process in a Multi-Dimension Networks: Generating, Modelling and Simulation.

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