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Newman01-SciCollabNetworks1

Newman01-SciCollabNetworks1 - Scientific collaboration...

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Unformatted text preview: Scientific collaboration networks. I. Network construction and fundamental results M. E. J. Newman Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501 and Center for Applied Mathematics, Cornell University, Rhodes Hall, Ithaca, New York 14853 ~ Received 5 December 2000; revised manuscript received 1 February 2001; published 28 June 2001 ! 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. DOI: 10.1103/PhysRevE.64.016131 PACS number ~ s ! : 89.75.Hc, 89.65. 2 s, 89.70. 1 c, 01.30. 2 y I. INTRODUCTION A social network @ 1,2 # is a set of people or groups each of which has connections of some kind to some or all of the others. In the language of social network analysis, the people or groups are called ‘‘actors’’ and the connections ‘‘ties.’’ Both actors and ties can be defined in different ways depend- ing on the questions of interest. An actor might be a single person, a team, or a company. A tie might be a friendship between two people, a collaboration or common member be- tween two teams, or a business relationship between compa- nies. Social network analysis has a history stretching back at least half a century, and has produced many results concern- ing social influence, social groupings, inequality, disease propagation, communication of information, and indeed al- most every topic that has interested 20th century sociology. The Physical Review is, however, a physics journal. Why should a physicist be interested in social networks? There has, in fact, been a substantial surge of interest in social networks within the physics community recently, as evi- denced by the large body of papers on the topic—see Refs. @ 3–24 # and references therein. The techniques of statistical physics in particular turn out to be well suited to the study of these networks. Profitable use has been made of a variety of physical modeling techniques @ 5–7 # , exact solutions @ 8–13 # , Monte Carlo simulation @ 14–17 # , scaling and renormaliza- tion group methods @ 15–17 # , mean-field theory @ 18,19 # , per- colation theory @ 20–22 # , the replica method @ 23 # , generating functions @ 20,22,24 # , and a host of other techniques familiar to the readers of this publication....
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