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Genetic programming in the twenty-first century: a bibliometric and content-based analysis from both sides of the fence

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Abstract

In this work we present an extensive bibliometric and content-based analysis of the scientific literature about genetic programming in the twenty-first century. Our work has two key peculiarities. First, we revealed the topics emerging from the literature based on an unsupervised analysis of the textual content of titles and abstracts. Second, we executed all of our analyses twice, once on the papers published in the venues that are typical of the evolutionary computation research community and once on those published in all the other venues. This view from “both sides of the fence” allows us to gain broader and deeper insights into the actual contributions of our community.

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Notes

  1. Formally, the twenty-first century started on January 1, 2001, rather than on January 1, 2000, which is the starting date of the so-called “2000s century.” We chose, however, to use “twenty-first century” because we think it is a more accessible locution.

  2. https://www.scopus.com.

  3. The publication venue is shown in the “source title” field of Scopus results.

  4. http://species-society.org, accessed on September 2018. SPECIES is a non-profit association that “aims to promote evolutionary algorithmic thinking within Europe and wider, and more generally to promote inspiration of parallel algorithms derived from natural processes”.

  5. Provided by the Computing Research and Education Association of Australasia, it is one among A\(^*\) (best), A, B, and C (worst), http://www.core.edu.au/conference-portal.

  6. Both lemmatization and stemming have been done using the NLTK toolkit, https://www.nltk.org/.

  7. Originally, countries of affiliation are a multiset as more than one author can be affiliated with an institution in the same country. We considered the corresponding set.

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Acknowledgements

This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia) under Project DSAIPA/DS/0022/2018 (GADgET). Mauro Castelli acknowledges the financial support from the Slovenian Research Agency (research core Funding No. P5-0410).

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Authors and Affiliations

  1. Department of Engineering and Architecture, University of Trieste, Trieste, Italy

    Andrea De Lorenzo, Alberto Bartoli & Eric Medvet

  2. NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal

    Mauro Castelli

  3. School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand

    Bing Xue

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  1. Andrea De Lorenzo
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Correspondence to Eric Medvet.

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De Lorenzo, A., Bartoli, A., Castelli, M. et al. Genetic programming in the twenty-first century: a bibliometric and content-based analysis from both sides of the fence. Genet Program Evolvable Mach 21, 181–204 (2020). https://doi.org/10.1007/s10710-019-09363-3

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