Influence diffusion, community detection, and link prediction in social network analysis

被引：0
作者：
机构：
[1] Department of Computer Science, University of Texas at Dallas, Richardson, TX
来源：
Du, D.-Z. (dzdu@utdallas.edu) | 1600年 / Springer Science and Business Media, LLC卷 / 51期
关键词：
Community detection; Influence diffusion; Link prediction; Social network analysis; Social networks;
D O I：
10.1007/978-1-4614-7582-8_11
中图分类号：
学科分类号：
摘要：
Social networks have received extensive attention among researchers across a wide range of disciplines such as computer science, physics, and sociology. This paper mainly overviews a variety of approaches for three problems in real-world life scenarios. The first problem is about influence diffusion, in which influence represents news, ideas, information, and so forth; the second one concerns with partitioning social networks into communities efficiently; and the third one is to predict the hidden or possible new links between individuals in the future based on the existing or observed information. © Springer Science+Business Media New York 2013.
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页码：305 / 325
页数：20
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