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Titlebook: Information and Influence Propagation in Social Networks; Wei Chen,Laks V. S. Lakshmanan,Carlos Castillo Book 2014 Springer Nature Switzer

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發(fā)表于 2025-3-21 17:08:12 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Information and Influence Propagation in Social Networks
編輯Wei Chen,Laks V. S. Lakshmanan,Carlos Castillo
視頻videohttp://file.papertrans.cn/466/465927/465927.mp4
叢書名稱Synthesis Lectures on Data Management
圖書封面Titlebook: Information and Influence Propagation in Social Networks;  Wei Chen,Laks V. S. Lakshmanan,Carlos Castillo Book 2014 Springer Nature Switzer
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
doihttps://doi.org/10.1007/978-3-031-01850-3
isbn_softcover978-3-031-00722-4
isbn_ebook978-3-031-01850-3Series ISSN 2153-5418 Series E-ISSN 2153-5426
issn_series 2153-5418
copyrightSpringer Nature Switzerland AG 2014
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 22:16:31 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:04:01 | 只看該作者
Learning Propagation Models,the propagation model. These studies focus on the problem of how to find a small number of seed nodes to activate at start, such that the expected number of network nodes that are activated when the propagation saturates is maximum.
地板
發(fā)表于 2025-3-22 07:06:25 | 只看該作者
Book 2014nline 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
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發(fā)表于 2025-3-22 11:38:48 | 只看該作者
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發(fā)表于 2025-3-22 15:54:36 | 只看該作者
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發(fā)表于 2025-3-22 19:17:16 | 只看該作者
Introduction,In this chapter we motivate the study of influence and information propagation by providing numerous examples. In addition, we provide some basic definitions.
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發(fā)表于 2025-3-22 22:27:10 | 只看該作者
Data and Software for Information/Influence: Propagation Research,Research on information and influence propagations is motivated by real-world applications. The availability of real-world datasets from such applications, or datasets that closely resemble them, is of utmost importance. Data is important to validate models about how viral phenomena unravel in practice under a variety of conditions.
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發(fā)表于 2025-3-23 01:45:11 | 只看該作者
Conclusion and Challenges,Most of the research covered in this book is motivated by practical applications. In addition, there is an implicit thesis underlying all this work: viral phenomena can not only be modeled accurately, but they can also be engineered. For instance, in the area of marketing, there is a certain expectation that a campaign can be designed to “..”
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發(fā)表于 2025-3-23 06:07:14 | 只看該作者
Synthesis Lectures on Data Managementhttp://image.papertrans.cn/i/image/465927.jpg
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