# What Do Citation Counts Measure? An Updated Review of Studies on Citations in Scientific Documents Published between 2006 and 2018

## 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.

## Key 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 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).

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Source: https://tomesphere.com/paper/1906.04588