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This shows how centrality measures are positively influenced when an author collaborates with other central authors.
First, we examine whether there is a general tendency of central authors in the coauthorship network to publish papers that are more successful than those of non-central authors.
That is, despite Lages' small number of publications, they were in collaboration with very influential and central authors.
From this result we can conclude that when an author collaborates with central authors with a high closeness, then this researcher also increases his own closeness to all other authors in the network.
For instance, we showed that using these metrics alone we were able to identify a central author that, apparently, is not active in the community anymore, and also active and prolific authors that are not considered as central authors.
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Second, an author that is not in the top 30 publishers in SBRC, José Neuman de Souza (17 publications in SBRC), is the most central author according to both centrality metrics.
According to New York magazine's Gabriel Sherman, the statement's central author was Roger Ailes.
And, for all the help on the acceptance speech that Nixon got from Price, Buchanan, and Gavin, its central author was Richard Nixon.
The service allows authors to upload chapters and stories to a central author page (here's mine) and stories percolate to the top based on popularity and likes.
Therefore, a collaboration with a central author made Lages closer to another author that was not his direct collaborator.
This suggests that in sparse ego networks, the central author have more control on their collaborators being more selective in their recruitment and concluding that this behaviour has positive implications in the research impact.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com