What Do Citation Counts Measure? An Updated Review of Studies on Citations in Scientific Documents Published between 2006 and 2018
Iman Tahamtan, Lutz Bornmann

TL;DR
This paper reviews studies from 2006 to 2018 on citation analysis, highlighting advances in computational methods, citation context, and motivation, revealing diverse reasons for citations and emphasizing the importance of multiple features for understanding citation behavior.
Contribution
It updates prior reviews by including recent studies with advanced computational techniques and provides insights into citation functions, contexts, and motivations in scientific documents.
Findings
Citation reasons vary widely, including scientific and non-scientific motives.
Recent studies leverage machine learning for citation function recognition.
Analyzing citation context, semantics, and polarity enhances understanding of citation behavior.
Abstract
The purpose of this paper is to update the review of Bornmann and Daniel (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…
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