| 书目名称 | Information and Influence Propagation in Social Networks | | 编辑 | Wei Chen,Laks V. S. Lakshmanan,Carlos Castillo | | 视频video | | | 丛书名称 | Synthesis Lectures on Data Management | | 图书封面 |  | | 描述 | Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking,etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detaile | | 出版日期 | Book 2014 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01850-3 | | isbn_softcover | 978-3-031-00722-4 | | isbn_ebook | 978-3-031-01850-3Series ISSN 2153-5418 Series E-ISSN 2153-5426 | | issn_series | 2153-5418 | | copyright | Springer Nature Switzerland AG 2014 |
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发表于 2025-3-21 17:08:12
