MANUSCRIPT ABSTRACT: The analysis of citations to scientific publications has become a tool in the evaluation of a researcher’s work, especially due to an ever-increasing production volume. Despite its acknowledged shortcomings and the ongoing debate on their meaning, citations are still primarily viewed as endorsements and as indicators of the influence of the reference on the citing paper, regardless of e.g. the context of the citation. However, only recently has attention been given to the connection between contextual information and success of citing and cited papers, primarily because of the lack of extensive databases covering both types of metadata. We address this issue by studying the usage of citations in the full text of 156,000 articles in PLOS and tracing their bibliometric history from among 60 million records from the Web of Science. We find universal patterns of variation in the usage of citations across sections. Significantly, we find differences in micro-level citation patterns depending on the ultimate impact of the citing paper itself: Publications from high impact groups tend to select younger references, more very young references, as well as better-cited ones. Our study provides a quantitative approach to addressing the long-standing issue that not all citations count the same. MANUSCRIPT CITATION: Poncela-Casasnovas, J., Gerlach, M., Aguirre, N. et al. Large-scale analysis of micro-level citation patterns reveals nuanced selection criteria. Nat Hum Behav 3, 568–575 (2019) doi:10.1038/s41562-019-0585-7

Last modified

• 01/07/2020

Creator

• Julia Poncela-Casasnovas: julia.poncela@northwestern.edu
• Luis A Nunes Amaral: amaral@northwestern.edu
• Martin Gerlach: martin.gerlach@northwestern.edu
• Nathan Aguirre: siplacet@gmail.com

DOI

• https://doi.org/10.21985/N21X9J

Publisher

• Nature Human Behaviour,

Keyword

• science of science
• data science
• PLOS journals
• Web of Science
• data visualization
• citation patterns

Date created

• 2019-01-29

Related url

•  https://doi.org/10.1038/s41562-019-0585-7

Resource type

• Dataset

Rights statement

• No Copyright - Non-Commercial Use Only