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Immediate Computable Access to Curated Contributed Data

Coauthorships in Network Science Network

Weighted network of coauthorships between scientists working on network science

Weighted network of coauthorships between scientists working on network theory and experiment with edge weight indicating the strength of the collaboration between pairs of individuals.

(1589 vertices, 2742 edges)

Examples

Basic Examples

Retrieve the graph:

In[1]:=
ResourceData["Coauthorships in Network Science Network"]
Out[1]=

Summary properties:

In[2]:=
ResourceData["Coauthorships in Network Science Network", All]["Summary"]
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Basic Applications

Pick the author with the most collaborations:

In[3]:=
g = ResourceData["Coauthorships in Network Science Network"];
In[4]:=
author = First[MaximalBy[VertexList[g], VertexDegree[g, #] &]]
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Visualize the network around the author with the most collaborations:

In[5]:=
NeighborhoodGraph[g, author, Sequence[ VertexLabels -> {author -> Placed["Name", Above]}, VertexStyle -> (author -> Red), EdgeStyle -> Opacity[0.4]]]
Out[5]=

Wolfram Research, "Coauthorships in Network Science Network" from the Wolfram Data Repository (2019)  

Data Resource History

  • Date Created:

Source Metadata

  • Citation:
    • M. E. J. Newman, Finding community structure in networks using the eigenvectors of matrices, Phys. Rev. E 74, 036104 (2006).

Data Downloads

Publisher Information

  • Prepared for the Wolfram Data Repository By: Wolfram
  • Publisher of Record: Wolfram Research