Applied physics in Mexico: mining the past to predict the future

J. Antonio Río (), J. M. Russell and Daniela Juárez
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J. Antonio Río: Universidad Nacional Autónoma de México
J. M. Russell: Universidad Nacional Autónoma de México
Daniela Juárez: Universidad Nacional Autónoma de México

Scientometrics, 2020, vol. 125, issue 1, No 9, 187-212

Abstract: Abstract The development of the scientific output of Mexico in Applied Physics is explored from 1973 to 2017 in the Web of Science using traditional bibliometric indicators such as prolific authors and institutions; collaborating countries; journal preferences. A total of 9078 documents in the subject category of Applied Physics were retrieved and analyzed in five periods: 1973–1985, 1986–1995, 1996–2005, 2006–2010 and 2011–2017. Main findings point to an exponential increase in the production of Mexican papers over the 45 years of our study but with some slowing down in the first decade of the present century. A diversity of authors both national and foreign were identified but production found to be highly concentrated in five Mexican institutions. Journals were mainly those in basic sciences of Physics, Material Science, and Optics but with Energy and Fuels, and Radiology, Nuclear Medicine and Medical Imaging appearing around the turn of the century. In a second part of the study a text mining technique is used to determine the most frequently occurring words in the abstracts of the documents from 1985 onwards. In a similar exercise the main words found in the 911 literature reviews published worldwide in the category of Applied Physics during 2014, were examined with the purpose of providing relevant information for deciding on the desired path for future Mexican research in this area. Our results suggest that national efforts in this category are aligned with international interests in nanotechnology, particularly with respect to renewable and sustainable energy resources and mainly solar energy technology.

Keywords: Scientific output; Research trends; Nanotechnology; Solar energy; Data mining (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11192-020-03639-7

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