Hidden Bibliographic Details
| Other authors / contributors: | Kawash, Jalal, editor.
Agarwal, Nitin, editor.
Özyer, Tansel, editor.
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| ISBN: | 9783319510491
3319510495
9783319510484
3319510487
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| Digital file characteristics: | text file PDF
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| Notes: | Online resource; title from PDF title page (EBSCO, viewed March 24, 2017).
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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.
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| Other form: | Print version: Prediction and inference from social networks and social media. Cham : Springer, 2017 3319510487 9783319510484
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| Standard no.: | 10.1007/978-3-319-51049-1
10.1007/978-3-319-51
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