Literature DB >> 11461355

Scientific collaboration networks. I. Network construction and fundamental results.

M E Newman1.   

Abstract

Using computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. We study a variety of statistical properties of our networks, including numbers of papers written by authors, numbers of authors per paper, numbers of collaborators that scientists have, existence and size of a giant component of connected scientists, and degree of clustering in the networks. We also highlight some apparent differences in collaboration patterns between the subjects studied. In the following paper, we study a number of measures of centrality and connectedness in the same networks.

Year:  2001        PMID: 11461355     DOI: 10.1103/PhysRevE.64.016131

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  91 in total

Review 1.  Community structure in social and biological networks.

Authors:  M Girvan; M E J Newman
Journal:  Proc Natl Acad Sci U S A       Date:  2002-06-11       Impact factor: 11.205

2.  Searching for intellectual turning points: progressive knowledge domain visualization.

Authors:  Chaomei Chen
Journal:  Proc Natl Acad Sci U S A       Date:  2004-01-14       Impact factor: 11.205

3.  Classification of scale-free networks.

Authors:  Kwang-Il Goh; Eulsik Oh; Hawoong Jeong; Byungnam Kahng; Doochul Kim
Journal:  Proc Natl Acad Sci U S A       Date:  2002-09-18       Impact factor: 11.205

4.  Food-web structure and network theory: The role of connectance and size.

Authors:  Jennifer A Dunne; Richard J Williams; Neo D Martinez
Journal:  Proc Natl Acad Sci U S A       Date:  2002-09-16       Impact factor: 11.205

Review 5.  The architecture of complex weighted networks.

Authors:  A Barrat; M Barthélemy; R Pastor-Satorras; A Vespignani
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-08       Impact factor: 11.205

6.  Defining and identifying communities in networks.

Authors:  Filippo Radicchi; Claudio Castellano; Federico Cecconi; Vittorio Loreto; Domenico Parisi
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-23       Impact factor: 11.205

7.  The simultaneous evolution of author and paper networks.

Authors:  Katy Börner; Jeegar T Maru; Robert L Goldstone
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-19       Impact factor: 11.205

8.  Quantifying the impact of weak, strong, and super ties in scientific careers.

Authors:  Alexander Michael Petersen
Journal:  Proc Natl Acad Sci U S A       Date:  2015-08-10       Impact factor: 11.205

9.  PhysarumSpreader: A New Bio-Inspired Methodology for Identifying Influential Spreaders in Complex Networks.

Authors:  Hongping Wang; Yajuan Zhang; Zili Zhang; Sankaran Mahadevan; Yong Deng
Journal:  PLoS One       Date:  2015-12-18       Impact factor: 3.240

10.  Comparative analysis of false discovery rate methods in constructing metabolic association networks.

Authors:  Imhoi Koo; Sen Yao; Xiang Zhang; Seongho Kim
Journal:  J Bioinform Comput Biol       Date:  2014-08-07       Impact factor: 1.122

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