Literature DB >> 19628859

Predicting the behavior of techno-social systems.

Alessandro Vespignani1.   

Abstract

We live in an increasingly interconnected world of techno-social systems, in which infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. Examples are provided by the Internet, the World Wide Web, WiFi communication technologies, and transportation and mobility infrastructures. The multiscale nature and complexity of these networks are crucial features in understanding and managing the networks. The accessibility of new data and the advances in the theory and modeling of complex networks are providing an integrated framework that brings us closer to achieving true predictive power of the behavior of techno-social systems.

Mesh:

Year:  2009        PMID: 19628859     DOI: 10.1126/science.1171990

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  89 in total

1.  Complex systems: Spotlight on mobility.

Authors:  Dirk Brockmann
Journal:  Nature       Date:  2012-04-04       Impact factor: 49.962

2.  Persistence and uncertainty in the academic career.

Authors:  Alexander M Petersen; Massimo Riccaboni; H Eugene Stanley; Fabio Pammolli
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-19       Impact factor: 11.205

3.  Robust classification of salient links in complex networks.

Authors:  Daniel Grady; Christian Thiemann; Dirk Brockmann
Journal:  Nat Commun       Date:  2012-05-29       Impact factor: 14.919

4.  Critical effect of dependency groups on the function of networks.

Authors:  Roni Parshani; Sergey V Buldyrev; Shlomo Havlin
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-29       Impact factor: 11.205

5.  Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification.

Authors:  Nan Chen; Andrew J Majda
Journal:  Entropy (Basel)       Date:  2018-07-04       Impact factor: 2.524

6.  Understanding metropolitan patterns of daily encounters.

Authors:  Lijun Sun; Kay W Axhausen; Der-Horng Lee; Xianfeng Huang
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-05       Impact factor: 11.205

7.  Invasion threshold in structured populations with recurrent mobility patterns.

Authors:  Duygu Balcan; Alessandro Vespignani
Journal:  J Theor Biol       Date:  2011-10-19       Impact factor: 2.691

8.  Tracking employment shocks using mobile phone data.

Authors:  Jameson L Toole; Yu-Ru Lin; Erich Muehlegger; Daniel Shoag; Marta C González; David Lazer
Journal:  J R Soc Interface       Date:  2015-06-06       Impact factor: 4.118

9.  Dynamic population mapping using mobile phone data.

Authors:  Pierre Deville; Catherine Linard; Samuel Martin; Marius Gilbert; Forrest R Stevens; Andrea E Gaughan; Vincent D Blondel; Andrew J Tatem
Journal:  Proc Natl Acad Sci U S A       Date:  2014-10-27       Impact factor: 11.205

Review 10.  Non-pharmaceutical interventions during the COVID-19 pandemic: A review.

Authors:  Nicola Perra
Journal:  Phys Rep       Date:  2021-02-13       Impact factor: 25.600

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