Coauthors. Groups Number of Authors Avg. Degree Modularity Density Avg. Clustering

Coauthors. Groups Number of Authors Avg. Degree Modularity Density Avg. Clustering Coefficient Number of Communities Avg. Path LengthLasalocid (sodium) web primary Authors and All Coauthors Laureates NonLaureates Laureates NonLaureates 20649 27789 32.940 23.115 0.795 0.914 0.002 0.001 0.870 0.863 40 55 3.996 4.Primary Authors Only 68 68 3.912 1.118 0.656 0.828 0.058 0.017 0.459 0.441 29 39 fpsyg.2017.00209 2.962 3.Network measures for “primary authors and all coauthors” are represented visually in Fig 1; Measures for “primary authors only” represented in Fig 2. The degree distributions are non-normal and highly right skewed. Therefore, the non-parametric independent samples Mann-Whitney test was used to test for statistical significance. Results for “primary authors fpsyg.2014.00726 and all coauthors” are U = 284308736, Z = -1.710, Sig = 0.087. Results for “primary authors only” are U = 1712.5, Z = -2.747, Sig = 0.006. Numbers for “primary authors only” were calculated after filtering for nodes and edges between primary authors separately for each group. doi:10.1371/journal.pone.0134164.tThe extent of connectivity among the Laureates is even more notable when the two groups of authors are placed into a single network. Fig 3 shows the combined coauthor relations among the Laureates and the non-Laureates (some of whom have also co-authored). The figure shows the dominance of the Laureates (scarlet) in terms of centrality, as well as the intensity of their interconnection to one another, compared to the non-Laureates (grey). In summary, the Laureate networks reveal significant differences in social cohesion than the non-Laureate networks. The Laureate networks appear to be more interconnected, with many more bridging opportunities realized. They are less modular (tightly bonded into communities) and could be considered more open to the possibility of new connections; their lower modularity suggests the potentiality for greater flexibility, or reconfigurability. The Laureate networks appear to be highly attractive to other ambitious collaborators, suggesting the operation of the Matthew effect noted by Azoulay et al. [11].CBIC2 web DiscussionA relevant question for this study has been: does the Nobel network have higher social capital? We found that appropriately matched groups showed significant differences in relevant measures. The non-Laureates tend to be more productive and they have far more coauthors over the course of their careers. From these measures, we might conclude that appropriately matched non-Laureates make more attractive collaborators than the Laureates. However, despite absolute numbers, the two groups have very similar rates of collaboration per paper, both domestic and international (average number of coauthors and nations per paper). We also found very similar rates of first and last authorship, indicating that the groups are both highly visible in terms of name order recognition and demonstrate high levels of leadership, i.e. first or last author position. These similarities would seem to suggest that appropriately matched non-Laureates exercise very similar levels of social capital to their Prize winning counterparts. Indeed, at this level of analysis, the similarities outweigh the differences. Ending the analysis here would suggest very few differences. But that is not the whole story. The bibliometric analysis revealed two key differences. First, Laureates are more highly cited, despite roughly equivalent one-to-one matching by h-index. This may indicate that Laureates focus on fe.Coauthors. Groups Number of Authors Avg. Degree Modularity Density Avg. Clustering Coefficient Number of Communities Avg. Path LengthPrimary Authors and All Coauthors Laureates NonLaureates Laureates NonLaureates 20649 27789 32.940 23.115 0.795 0.914 0.002 0.001 0.870 0.863 40 55 3.996 4.Primary Authors Only 68 68 3.912 1.118 0.656 0.828 0.058 0.017 0.459 0.441 29 39 fpsyg.2017.00209 2.962 3.Network measures for “primary authors and all coauthors” are represented visually in Fig 1; Measures for “primary authors only” represented in Fig 2. The degree distributions are non-normal and highly right skewed. Therefore, the non-parametric independent samples Mann-Whitney test was used to test for statistical significance. Results for “primary authors fpsyg.2014.00726 and all coauthors” are U = 284308736, Z = -1.710, Sig = 0.087. Results for “primary authors only” are U = 1712.5, Z = -2.747, Sig = 0.006. Numbers for “primary authors only” were calculated after filtering for nodes and edges between primary authors separately for each group. doi:10.1371/journal.pone.0134164.tThe extent of connectivity among the Laureates is even more notable when the two groups of authors are placed into a single network. Fig 3 shows the combined coauthor relations among the Laureates and the non-Laureates (some of whom have also co-authored). The figure shows the dominance of the Laureates (scarlet) in terms of centrality, as well as the intensity of their interconnection to one another, compared to the non-Laureates (grey). In summary, the Laureate networks reveal significant differences in social cohesion than the non-Laureate networks. The Laureate networks appear to be more interconnected, with many more bridging opportunities realized. They are less modular (tightly bonded into communities) and could be considered more open to the possibility of new connections; their lower modularity suggests the potentiality for greater flexibility, or reconfigurability. The Laureate networks appear to be highly attractive to other ambitious collaborators, suggesting the operation of the Matthew effect noted by Azoulay et al. [11].DiscussionA relevant question for this study has been: does the Nobel network have higher social capital? We found that appropriately matched groups showed significant differences in relevant measures. The non-Laureates tend to be more productive and they have far more coauthors over the course of their careers. From these measures, we might conclude that appropriately matched non-Laureates make more attractive collaborators than the Laureates. However, despite absolute numbers, the two groups have very similar rates of collaboration per paper, both domestic and international (average number of coauthors and nations per paper). We also found very similar rates of first and last authorship, indicating that the groups are both highly visible in terms of name order recognition and demonstrate high levels of leadership, i.e. first or last author position. These similarities would seem to suggest that appropriately matched non-Laureates exercise very similar levels of social capital to their Prize winning counterparts. Indeed, at this level of analysis, the similarities outweigh the differences. Ending the analysis here would suggest very few differences. But that is not the whole story. The bibliometric analysis revealed two key differences. First, Laureates are more highly cited, despite roughly equivalent one-to-one matching by h-index. This may indicate that Laureates focus on fe.

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