On the application of machine learning in astronomy and astrophysics: A text-mining-based scientometric analysis
Metadatos
Afficher la notice complèteAuteur
Rodríguez, José VíctorEditorial
Wiley
Materia
Astronomy Astrophysics Machine learning Scientometrics Text mining
Date
2022-08-12Referencia bibliográfica
Rodríguez, J.-V., Rodríguez-Rodríguez, I., & Woo, W. L. (2022). On the application of machine learning in astronomy and astrophysics: A text-mining-based scientometric analysis. WIREs Data Mining and Knowledge Discovery, 12( 5), e1476. [https://doi.org/10.1002/widm.1476]
Résumé
Since the beginning of the 21st century, the fields of astronomy and astrophysics
have experienced significant growth at observational and computational levels,
leading to the acquisition of increasingly huge volumes of data. In order to process
this vast quantity of information, artificial intelligence (AI) techniques are being
combined with data mining to detect patterns with the aim of modeling, classifying
or predicting the behavior of certain astronomical phenomena or objects.
Parallel to the exponential development of the aforementioned techniques, the
scientific output related to the application of AI and machine learning (ML) in
astronomy and astrophysics has also experienced considerable growth in recent
years. Therefore, the increasingly abundant articles make it difficult to monitor
this field in terms of which research topics are the most prolific or novel, or which
countries or authors are leading them. In this article, a text-mining-based
scientometric analysis of scientific documents published over the last three
decades on the application of AI and ML in the fields of astronomy and astrophysics
is presented. The VOSviewer software and data from the Web of Science
(WoS) are used to elucidate the evolution of publications in this research field,
their distribution by country (including co-authorship), the most relevant topics
addressed, and the most cited elements and most significant co-citations according
to publication source and authorship. The obtained results demonstrate how
application of AI/ML to the fields of astronomy/astrophysics represents an
established and rapidly growing field of research that is crucial to obtaining
scientific understanding of the universe.