What do citation counts measure? An updated review of studies on citations in scientific documents published between 2006 and 2018

The purpose of this paper is to update the review of Bornmann and Daniel (J Doc 64(1):45–80, 2008 ) presenting a narrative review of studies on citations in scientific documents. The current review covers 41 studies published between 2006 and 2018. Bornmann and Daniel (2008) focused on earlier years...

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Vydáno v:	Scientometrics Ročník 121; číslo 3; s. 1635 - 1684
Hlavní autoři:	Tahamtan, Iman, Bornmann, Lutz
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.12.2019 Springer Nature B.V
Témata:	Accords Citation analysis Citations Computer applications Computer Science Context Contextual analysis Data mining Empirical analysis Information processing Information retrieval Information Storage and Retrieval Language patterns Learning algorithms Library Science Machine learning Motivation Polarity Retrieval Scientific papers Semantics Citation classification Citation behavior Citation analysis Citation counts Machine learning Information retrieval Citation function In-text citation Citation context Content analysis
ISSN:	0138-9130, 1588-2861
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Abstract	The purpose of this paper is to update the review of Bornmann and Daniel (J Doc 64(1):45–80, 2008 ) presenting a narrative review of studies on citations in scientific documents. The current review covers 41 studies published between 2006 and 2018. Bornmann and Daniel (2008) focused on earlier years. The current review describes the (new) studies on citation content and context analyses as well as the studies that explore the citation motivation of scholars through surveys or interviews. One focus in this paper is on the technical developments in the last decade, such as the richer meta-data available and machine-readable formats of scientific papers. These developments have resulted in citation context analyses of large datasets in comprehensive studies (which was not possible previously). Many studies in recent years have used computational and machine learning techniques to determine citation functions and polarities, some of which have attempted to overcome the methodological weaknesses of previous studies. The automated recognition of citation functions seems to have the potential to greatly enhance citation indices and information retrieval capabilities. Our review of the empirical studies demonstrates that a paper may be cited for very different scientific and non-scientific reasons. This result accords with the finding by Bornmann and Daniel (2008). The current review also shows that to better understand the relationship between citing and cited documents, a variety of features should be analyzed, primarily the citation context, the semantics and linguistic patterns in citations, citation locations within the citing document, and citation polarity (negative, neutral, positive).
AbstractList	The purpose of this paper is to update the review of Bornmann and Daniel (J Doc 64(1):45–80, 2008) presenting a narrative review of studies on citations in scientific documents. The current review covers 41 studies published between 2006 and 2018. Bornmann and Daniel (2008) focused on earlier years. The current review describes the (new) studies on citation content and context analyses as well as the studies that explore the citation motivation of scholars through surveys or interviews. One focus in this paper is on the technical developments in the last decade, such as the richer meta-data available and machine-readable formats of scientific papers. These developments have resulted in citation context analyses of large datasets in comprehensive studies (which was not possible previously). Many studies in recent years have used computational and machine learning techniques to determine citation functions and polarities, some of which have attempted to overcome the methodological weaknesses of previous studies. The automated recognition of citation functions seems to have the potential to greatly enhance citation indices and information retrieval capabilities. Our review of the empirical studies demonstrates that a paper may be cited for very different scientific and non-scientific reasons. This result accords with the finding by Bornmann and Daniel (2008). The current review also shows that to better understand the relationship between citing and cited documents, a variety of features should be analyzed, primarily the citation context, the semantics and linguistic patterns in citations, citation locations within the citing document, and citation polarity (negative, neutral, positive). The purpose of this paper is to update the review of Bornmann and Daniel (J Doc 64(1):45–80, 2008 ) presenting a narrative review of studies on citations in scientific documents. The current review covers 41 studies published between 2006 and 2018. Bornmann and Daniel (2008) focused on earlier years. The current review describes the (new) studies on citation content and context analyses as well as the studies that explore the citation motivation of scholars through surveys or interviews. One focus in this paper is on the technical developments in the last decade, such as the richer meta-data available and machine-readable formats of scientific papers. These developments have resulted in citation context analyses of large datasets in comprehensive studies (which was not possible previously). Many studies in recent years have used computational and machine learning techniques to determine citation functions and polarities, some of which have attempted to overcome the methodological weaknesses of previous studies. The automated recognition of citation functions seems to have the potential to greatly enhance citation indices and information retrieval capabilities. Our review of the empirical studies demonstrates that a paper may be cited for very different scientific and non-scientific reasons. This result accords with the finding by Bornmann and Daniel (2008). The current review also shows that to better understand the relationship between citing and cited documents, a variety of features should be analyzed, primarily the citation context, the semantics and linguistic patterns in citations, citation locations within the citing document, and citation polarity (negative, neutral, positive).
Author	Bornmann, Lutz Tahamtan, Iman
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Snippet	The purpose of this paper is to update the review of Bornmann and Daniel (J Doc 64(1):45–80, 2008 ) presenting a narrative review of studies on citations in... The purpose of this paper is to update the review of Bornmann and Daniel (J Doc 64(1):45–80, 2008) presenting a narrative review of studies on citations in...
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SubjectTerms	Accords Citation analysis Citations Computer applications Computer Science Context Contextual analysis Data mining Empirical analysis Information processing Information retrieval Information Storage and Retrieval Language patterns Learning algorithms Library Science Machine learning Motivation Polarity Retrieval Scientific papers Semantics
Title	What do citation counts measure? An updated review of studies on citations in scientific documents published between 2006 and 2018
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