Information Cascade Analysis
Information Cascade Analysis is a computational framework within social network mining that models the propagation dynamics of information across a network by identifying and analyzing the sequence and structure of adoption events to distinguish influence-driven diffusion from independent behavior.
149
Publications
17.6K
Citations
408
Authors
222
Institutions
Publications per year
2017–2026
49
Parents
149
Eytan Bakshy, Jake M. Hofman, Winter Mason et al. · 2011 · 1.7K citations
Patterns of Cascading Behavior in Large Blog Graphs
Jure Leskovec, Mary McGlohon, Christos Faloutsos et al. · 2007 · 566 citations
1–5 of 149
408
National Bureau of Economic Research, United States
4 publications · 10.5K citations
5
h-index
4
h-index
University of California, Los Angeles, United States
4 publications · 10.5K citations
4
h-index
4
h-index
3
h-index
1–5 of 408
222
Kitasato University
Tokyo, Japan
5 h-index
4 publications
79 citations
University of California, Los Angeles
Los Angeles, United States
5 h-index
7 publications
7.5K citations
Tsinghua University
Beijing, China
4 h-index
15 publications
588 citations

National Taiwan University
Taipei, Taiwan
4 h-index
9 publications
201 citations
University of Oxford
Oxford, United Kingdom
4 h-index
4 publications
112 citations
Max Planck Institute for Software Systems
Saarbrücken, Germany
4 h-index
6 publications
545 citations
The Ohio State University
Columbus, United States
3 h-index
3 publications
74 citations
University of Virginia
Charlottesville, United States
3 h-index
3 publications
502 citations
1–8 of 222
Repository · 6 publications · 6.8K citations
6
h-index
5 publications · 82 citations
5
h-index
Repository · 4 publications · 168 citations
4
h-index
4 publications · 735 citations
4
h-index
2 publications · 88 citations
2
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1–5