Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality.

By Mark Newman. Physical review. E, Statistical, nonlinear, and soft matter physics, 2000

2,517 citations recorded by the source corpus.

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. Here we study a variety of nonlocal statistics for these networks, such as typical distances between scientists through the network, and measures of centrality such as closeness and betweenness. We further argue that simple networks such as these cannot capture variation in the strength of collaborative ties and propose a measure of collaboration strength based on the number of papers coauthored by pairs of scientists, and the number of other scientists with whom they coauthored those papers.

Subfields: Computer Networks and Communications, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/e0be3cae5ba94cef9426d6b9849bbfcdd572ac94

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In Computer Networks and Communications

In Molecular Biology

In Statistical and Nonlinear Physics

Citations in the corpus

E-Mail as Spectroscopy: Automated Discovery of Community Structure within Organizations (2003, methodology): “To do this uickly, we used the fast algorithm of Brandes [Brandes, 2001, Newman, 2001, irvan and Newman, 2002], whose basic strategy is the following: Consider the hortest paths between a single vertex, the “center”, and all other vertices. alculate the betweenness of each edge due only to these…”
Potential banana skins in animal social network analysis (2009, background): “Newman (2001) suggested that group size could be included by adding 1/(g-1), not 1, to the tie strength of each pair of animals seen in a group of size g.”
The rise of Network Ecology: Maps of the topic diversity and scientific collaboration (2013, methodology): “…to bibliometric studies have been used successfully to characterize the social structure of collaboration in many fields, including sociology (Moody, 2004), physics, biomedical research, and computer science (Newman, 2001a, 2001b), and the study of ecosystem services (Costanza & Kubiszewski, 2012).”
Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs (2004, background): “collaboration network examined by Newman, 2001a, 2001b deals with both collaborations and papers).”
Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks (2011, background): “…(Bordons & Gómez, 2000; Glänzel, 2002; Glänzel & Schubert, 2004); social network analysis/network science (Barabási et al., 2002; Kretschmer, 1997; Newman, 2001c, 2004a; Wagner, 2008; Wagner & Leydesdorff, 2005); qualitative methods of observation and interviews (Hara et al., 2003; Shrum et al.,…”
Clustering and preferential attachment in growing networks. (2001, background): “The principal reason for this has been the lack of good time-resolved data on how networks grow.”
Synchronization in complex networks (2008, background): “Indeed, many complex networks where synchronization is relevant are actually weighted and display a highly heterogeneous distribution of both degrees and weights (Barrat et al., 2004; Braunstein et al., 2003; Newman, 2001; Yook et al., 2001).”
Random graphs with arbitrary degree distributions and their applications. (2000, background): “For some networks at least, this gives a surprisingly good estimate of the true average distance [37].”