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Titlebook: Social Network Analysis - Community Detection and Evolution; Rokia Missaoui,Idrissa Sarr Book 2014 Springer International Publishing Switz

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發(fā)表于 2025-3-21 19:39:29 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Social Network Analysis - Community Detection and Evolution
編輯Rokia Missaoui,Idrissa Sarr
視頻videohttp://file.papertrans.cn/870/869748/869748.mp4
概述Describes novel results in community detection and/or evolution.Clearly written and generously illustrated.Covers hot topics in social network such as community evolution, information propagation and
叢書名稱Lecture Notes in Social Networks
圖書封面Titlebook: Social Network Analysis - Community Detection and Evolution;  Rokia Missaoui,Idrissa Sarr Book 2014 Springer International Publishing Switz
描述This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edited work will appeal to researchers, practitioners and students interested in the latest developments of social network analysis.
出版日期Book 2014
關鍵詞Identification of Cohesive Groups; Influence Detection and Maximization; Information Propagation; Key P
版次1
doihttps://doi.org/10.1007/978-3-319-12188-8
isbn_softcover978-3-319-38474-0
isbn_ebook978-3-319-12188-8Series ISSN 2190-5428 Series E-ISSN 2190-5436
issn_series 2190-5428
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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Lecture Notes in Social Networkshttp://image.papertrans.cn/s/image/869748.jpg
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https://doi.org/10.1007/978-3-319-12188-8Identification of Cohesive Groups; Influence Detection and Maximization; Information Propagation; Key P
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Hierarchical and Matrix Structures in a Large Organizational Email Network: Visualization and Modeldeling organizational hierarchies within large, complex network datasets. In the first part of the paper, we find that visualization and interpretation of complex organizational network data is facilitated by integration of network data with information on formal organizational divisions and levels.
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Overlaying Social Networks of Different Perspectives for Inter-network Community Evolution, ones. Even though individuals may belong to a social network with a very precise type of links such as professional ties in ., the interactions that may happen in other social networks such as . are not reflected in the original network. We believe that overlaying networks with various types of lin
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