James P. Bagrow
Statistical and Nonlinear Physics · 2004–2014
A researcher in the Science corpus: 6 papers; trusts 15 researchers and is trusted by 45 researchers here, as inferred from the citation graph.
Subfields
- Statistical and Nonlinear Physics — 63 citations into it; #535 of 10,127 by trust here, #1,075 by citations
- Molecular Biology — 28 citations into it; #1,653 of 17,773 by trust here, #7,298 by citations
- Transportation — 11 citations into it
- Computer Networks and Communications — 9 citations into it
- Economics and Econometrics — 7 citations into it
- Experimental and Cognitive Psychology — 7 citations into it
- Modeling and Simulation — 7 citations into it
- Computational Theory and Mathematics — 5 citations into it
Whom James P. Bagrow trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- Michelle Girvan
- Albert-László Barabási
- Aaron Clauset
- Steven H. Strogatz
- Dirk Brockmann
- Réka Albert
- Chaoming Song
- Jukka-Pekka Onnela
- Duygu Balcan
Who trusts James P. Bagrow overall
- Santo Fortunato
- Jaewon Yang
- Jure Leskovec
- Susan Dina Ghiassian
- Michele Coscia
- Olaf Sporns
- Amanda L. Traud
- Luciano da Fontoura Costa
- Leon Danon
- Julian McAuley
Papers from James P. Bagrow's perspective
Ordered by how strongly the researchers James P. Bagrow trusts endorse each paper. Same corpus, a different order for every researcher.
- The Structure and Function of Complex Networks
- Exploring complex networks (Nature)
- Mixing patterns in networks. (Physical review. E, Statistical, nonlinear, and soft matter physics)
- The structure of scientific collaboration networks.
- Statistical mechanics of complex networks
- Finding community structure in very large networks. (Physical review. E, Statistical, nonlinear, and soft matter physics)
- Collective dynamics of ‘small-world’ networks
- Graph structure in the Web (Comput. Networks)
- Epidemic spreading in scale-free networks. (Physical Review Letters)
- Structure and tie strengths in mobile communication networks (Proceedings of the National Academy of Sciences of the United States of America)
Their papers
- Link communities reveal multiscale complexity in networks (2009) — 1,946 citations
- More Voices Than Ever? Quantifying Media Bias in Networks (2011) — 73 citations
- Human language reveals a universal positivity bias (2014) — 396 citations
- Flavor network and the principles of food (2011) — 312 citations
- Collective Response of Human Populations to Large-Scale Emergencies (2011) — 356 citations
- Local method for detecting communities. (2004) — 304 citations