Theoretical high energy physcis in Latin America from 1990 to 2012: a statistical study

Urrutia, Gerardo; Prado, Lilian; Bietenholz, Wolfgang

doi:10.1007/s11192-018-2739-1

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…Particle is the subfield with the highest number of publications, and it is also the subfield in which there has been the greatest growth. There is a sharp peak, in 2010, in this subfield curve—that can be attributed to the first ATLAS and Compact Muon Solenoid (CMS) publications (Aad et al, 2010), joined by theoretical publications (Urrutia Sánchez et al, 2018). All SCFs of the Study database can be accessed by the “Supporting Data” section link.…”

Section: Resultsmentioning

confidence: 95%

Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics

Pech

Delgado

Sorella

2022

Asso for Info Science & Tech

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Classifying papers according to the fields of knowledge is critical to clearly understand the dynamics of scientific (sub)fields, their leading questions, and trends. Most studies rely on journal categories defined by popular databases such as WoS or Scopus, but some experts find that those categories may not correctly map the existing subfields nor identify the subfield of a specific article. This study addresses the classification problem using data from each paper (Abstract, Title, Keywords, and the KeyWords Plus) and the help of experts to identify the existing subfields and journals exclusive of each subfield. These “exclusive journals” are critical to obtain, through a pattern detection procedure that uses machine learning techniques (from software NVivo), a list of the frequent terms that are specific to each subfield. With that list of terms and with the help of optimization procedures, we can identify to which subfield each paper most likely belongs. This study can contribute to support scientific policy‐makers, funding, and research institutions—via more accurate academic performance evaluations—, to support editors in their tasks to redefine the scopes of journals, and to support popular databases in their processes of refining categories.

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Section: Resultsmentioning

confidence: 95%

Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics

Pech

Delgado

Sorella

2022

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

How latecomers catch up to leaders in high-energy physics as Big Science: transition from national system to international collaboration

Jang

2019

Scientometrics

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Bibliometric mapping of microbiology research topics (2012–16): a comparison by socioeconomic development and infectious disease vulnerability values

Dehdarirad

Sotudeh

Freer

2019

FEMS Microbiology Letters

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Theoretical high energy physcis in Latin America from 1990 to 2012: a statistical study

Abstract: We present a statistical overview of the publications in theoretical high energy physics (HEP), which emerged in Latin America (LA) in the period from 1990 to 2012. Our study captures the eight Latin American nations, which are dominant in this field of research:

Cited by 3 publications

References 27 publications

Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics

Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics

How latecomers catch up to leaders in high-energy physics as Big Science: transition from national system to international collaboration

Bibliometric mapping of microbiology research topics (2012–16): a comparison by socioeconomic development and infectious disease vulnerability values

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