| 书目名称 | Prediction and Inference from Social Networks and Social Media |
| 编辑 | Jalal Kawash,Nitin Agarwal,Tansel Özyer |
| 视频video | |
| 概述 | 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 |
| 丛书名称 | Lecture Notes in Social Networks |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2017 |
| 关键词 | activity-based mood prediction; overlapping community structures; link prediction; modeling multi-dimen |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-51049-1 |
| isbn_softcover | 978-3-319-84553-1 |
| isbn_ebook | 978-3-319-51049-1Series ISSN 2190-5428 Series E-ISSN 2190-5436 |
| issn_series | 2190-5428 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 19:08:19
