Predictability of Scientific Success
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Papers

​​Quantifying the evolution of individual scientific impact

​Roberta Sinatra, Dashun Wang, Pierre Deville, Chaoming Song, Albert-László Barabási
Science, Vol. 354, Issue 6312 (2016)

​doi:10.1126/science.aaf5239
[pdf] [supp. information] [interactive visualization] [Nature video]

Featured in: ​New York Times, Science News, Nature News, The Scientist, Wired, Chronicle of Higher Education, Scientific American, Forbes
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​View full list of press coverage here. 
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Research funding goes to rich clubs

Michael Szell and Roberta Sinatra
Proceedings of the National Academy of Sciences, 112 48, 14749–14750 (2015)

​doi:10.1038/nphys3494
[pdf]
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A century of physics

Roberta Sinatra, Pierre Deville, Michael Szell, Dashun Wang, Albert-László Barabási
Nature Physics, 11 791 (2015)

​doi:10.1038/nphys3494
[pdf] [cover]
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Collective credit allocation in science

Hua-Wei Shen and Albert-László Barabási
Proceedings of the National Academy of Sciences, 1-6 (2014)
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doi:10.1073/pnas.1401992111
[pdf] [supp. information]
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Modeling and Predicting Popularity Dynamics via Reinforced Poisson Processes

​Huawei Shen, Dashun Wang, Chaoming Song, Albert-László Barabási
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 291-297 (2014)
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arXiv:1401.0778 [cs.SI]
[pdf]
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Quantifying Long-Term Scientific Impact

Dashun Wang, Chaoming Song, Albert-László Barabási
Science, 342, 127-131 (2013) 
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doi:10.1126/science.1237825
[pdf] [supp. information]
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Characterizing scientific production and consumption in Physics

​Qian Zhang, Nicola Perra, Bruno Gonçalves, Fabio Ciulla & Alessandro Vespignani
Scientific Reports 3, Article number: 1640 (2013)
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doi:10.1038/srep01640
[pdf]

Interactive Visualization
by Kim Albrecht et al
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Nature Video
by Mauro Martino et al
Click to view

Nature Physics cover
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October 2015

We acknowledge funding from AFOSR grant FA9550-15-1-0077
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Related links: Network Science Institute  |   CCNR   |   MOBS Lab

Banner visualizations by Kim Albrecht

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