Prediction and Inference from Social Networks and Social Media

Nonfiction, Science & Nature, Science, Other Sciences, System Theory, Computers, Database Management, General Computing
Cover of the book Prediction and Inference from Social Networks and Social Media by , Springer International Publishing
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Author: ISBN: 9783319510491
Publisher: Springer International Publishing Publication: March 16, 2017
Imprint: Springer Language: English
Author:
ISBN: 9783319510491
Publisher: Springer International Publishing
Publication: March 16, 2017
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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