2022
DOI: 10.1002/asi.24655
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Classifying papers into subfields using Abstracts, Titles, Keywords and KeyWords Plus through pattern detection and optimization procedures: An application in Physics

Abstract: 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 KeyWord… Show more

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Cited by 6 publications
(1 citation statement)
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“…Keywords plus are correlative keywords extracted from the titles of documents and their cited references, usually generated automatically by clustering algorithms, and not necessarily located in the title of the article or appearing as author keywords [70]. Many studies have shown that keywords plus are able to capture the content of the literature with greater depth and diversity than author keywords and are often employed as a key metric in the bibliometric analysis [71][72][73]. Keywords plus have also been widely applied to identify research trends and hotspots in many domains, such as climate change [74], air pollution [75], biomedicine [76], etc.…”
Section: Analysis Of Keyword Co-occurrencementioning
confidence: 99%
“…Keywords plus are correlative keywords extracted from the titles of documents and their cited references, usually generated automatically by clustering algorithms, and not necessarily located in the title of the article or appearing as author keywords [70]. Many studies have shown that keywords plus are able to capture the content of the literature with greater depth and diversity than author keywords and are often employed as a key metric in the bibliometric analysis [71][72][73]. Keywords plus have also been widely applied to identify research trends and hotspots in many domains, such as climate change [74], air pollution [75], biomedicine [76], etc.…”
Section: Analysis Of Keyword Co-occurrencementioning
confidence: 99%