The genetic programming collaboration network and its communities

@inproceedings{Luthi2007TheGP,
  title={The genetic programming collaboration network and its communities},
  author={Leslie Luthi and Marco Tomassini and Mario Giacobini and William B. Langdon},
  booktitle={GECCO '07},
  year={2007}
}
Useful information about scientific collaboration structures and patterns can be inferred from computer databases of published papers. The genetic programming bibliography is the most complete reference of papers on GP. In addition to locating publications, it contains coauthor and coeditor relationships from which a more complete picture of the field emerges. We treat these relationships as undirected small world graphs whose study reveals the community structure of the GP collaborative social… 
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References

SHOWING 1-10 OF 16 REFERENCES
The structure of the genetic programming collaboration network
TLDR
The genetic programming bibliography aims to be the most complete reference of papers on genetic programming and contains coauthor and coeditor relationships which have not previously been studied.
Scientific collaboration networks. I. Network construction and fundamental results.
  • M. Newman
  • Medicine, Engineering
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2001
TLDR
Using computer databases of scientific papers in physics, biomedical research, and computer science, a network of collaboration between scientists in each of these disciplines is constructed, and a number of measures of centrality and connectedness in the same networks are studied.
Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality.
  • M. Newman
  • Medicine, Physics
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2001
TLDR
It is argued that simple networks such as these cannot capture variation in the strength of collaborative ties and proposed a measure of collaboration strength based on the number of papers coauthored by pairs of scientists, and thenumber of other scientists with whom they coauthored those papers.
The Complex Network of Evolutionary Computation Authors: an Initial Study
TLDR
The network of authors of evolutionary computation papers found in a major bibliographic database is explored, its macroscopic properties are examined, and it is found that the EC co-authorship network yields results in the same ballpark as other networks, but exhibits some distinctive patterns in terms of internal cohesion.
Fast algorithm for detecting community structure in networks.
  • M. Newman
  • Computer Science, Medicine
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2004
TLDR
An algorithm is described which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster, than previous algorithms.
The Structure and Function of Complex Networks
  • M. Newman
  • Physics, Computer Science
    SIAM Rev.
  • 2003
TLDR
Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
The evolution of the mathematical research collaboration graph
TLDR
Some properties of the research collaboration graph for mathematicians, its evolution over time, and some random models that might produce graphs of this sort are discussed.
The complex network of EC authors
TLDR
An understanding of the structure of the network and what makes some nodes stand out goes beyond mere curiosity to give us some insight on the deep workings of science, what makes an author popular, or some co-authors preferred over others.
Social Network Analysis: A Handbook
Networks and Relations The Development of Social Network Analysis Handling Relational Data Lines, Direction and Density Centrality and Centralization Components, Cores, and Cliques Positions, Roles,
...
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