| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783319510491 |
| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783319510484 |
| DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Call number |
006.312 PR ED |
| TITLE STATEMENT |
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| Title |
Prediction and inference from social networks and social media |
| Statement of responsibility, etc |
edited by Jalal Kawash, Nitin Agarwal, Tansel Ozyer |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication |
Cham : |
| Publisher |
Springer International Publishing, |
| Date |
c2017. |
| PHYSICAL DESCRIPTION |
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| Extent |
ix, 225 p. : |
| Other Details |
ill. ; |
| Size |
25 cm. |
| SERIES STATEMENT |
|---|
| Series statement |
Lecture Notes in Social Networks, |
| International Standard Serial Number |
2190-5428. |
| CONTENTS |
|---|
| 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. |
| SUMMARY |
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| Summary |
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. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Computer science |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Data mining |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
User interfaces (Computer systems) |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Computers and civilization |
| ADDED ENTRY |
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| Name |
Kawash, Jalal, |
| Role |
Edited by |
| ADDED ENTRY |
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| Name |
Agarwal, Nitin, |
| Role |
Edited by |
| ADDED ENTRY |
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| Name |
Ozyer, Tansel, |
| Role |
Edited by |
| ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
https://uowd.box.com/s/vputfhdosh2virihawmxbswm3z4qgk21 |
| Public note |
Location Map |
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