Influence Maximization on Social Graphs: A Survey

Influence Maximization (IM), which selects a set of k users (called seed set) from a social network to maximize the expected number of influenced users (called influence spread), is a key algorithmic problem in social influence analysis. Due to its immense application potential and enormous technica...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering Jg. 30; H. 10; S. 1852 - 1872
Hauptverfasser:	Li, Yuchen, Fan, Ju, Wang, Yanhao, Tan, Kian-Lee
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.10.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	algorithm design Algorithms Classification algorithms Computational modeling Diffusion processes Influence maximization information diffusion Information dissemination Integrated circuit modeling Maximization Social network services Social networks Stochastic processes Taxonomy
ISSN:	1041-4347, 1558-2191
Online-Zugang:	Volltext
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