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b Degree centrality distribution of Facebook dataset.
d Degree centrality distribution of CA-GrQc dataset Fig. 4 Experimental results of directed datasets.
d Degree centrality distribution of Epinions-II dataset Fig. 5 Intersection similarity distances between Katz centrality and degree centrality.
For each of the four centrality metrics we test the null hypothesis that coauthorship centrality distributions of papers in P ↑ ( t ) and P ↓ ( t ) are the same against the alternative hypothesis that the centrality distribution of papers in P ↑ ( t ) is stochastically larger than that of papers in P ↓ ( t ).
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We test Hypothesis 1 by comparing coauthorship centrality distributions of papers in P ↑ ( t ) and P ↓ ( t ) for each year t.
We further compared degree/betweenness centrality distributions of the host domains targeted by DNA, RNA, and retrotranscribing viruses.
For a given network, a special probability distribution, namely the centrality distribution associated with the links of a network can be determined based on the number of the shortest paths passing through each link.
Regarding the former, one possible effect of a skewed node centrality distribution is to distinguish potential future hubs in our network of cortical units.
An appropriate change in the weight of a link alters the number of the shortest paths that pass through it, thereby modifying the centrality distribution.
The presence of such nodes is indicated by a more skewed distribution of node betweenness centrality (see Figure 9B; also Figure S3 for histograms of betweenness centrality distributions).
For longitudinal comparison of centralities, the distribution of betweenness value of sorted proteins has been indicated in Figure 4.
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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