Building bridges: the role of subfields in metaheuristics
ACM SIGEVOlution
The genetic programming collaboration network and its communities
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Where is evolutionary computation going? A temporal analysis of the EC community
Genetic Programming and Evolvable Machines
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The study of all kind of complex networks has undergone an accelerated expansion in the last few years, after the introduction of models for scale-free/power-law [2] and small-world [12] networks, which, in turn, has induced the study of many different phenomena under this new light. Co-authorship patterns are one of them. Nodes in co-authorship networks are paper authors, joined by edges if they have written at least one paper together. Even as most papers are written by a few authors staying at the same institution, science is a global business nowadays, and lots of papers are co-authored by scientists continents apart from each other. There are several interesting facts that can be computed on these co-authorship networks: first, what kind of macroscopic values they yield, and second, which are the most outstanding actors (authors) and edges (co-authorships) within this network. 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.