Psychology, Department of

 

Date of this Version

2019

Document Type

Article

Citation

Stevens, J.R. & Duque, J.F. (2019). Order matters: Alphabetizing in-text citations biases citation rates. Psychonomic Bulletin & Review, 26(3), 1020–1026

Abstract

Though citations are critical for communicating science and evaluating scholarly success, properties unrelated to the quality of the work—such as cognitive biases—can influence citation decisions. The primacy effect, in particular, is relevant to lists, which for in-text citations could result in citations earlier in the list receiving more attention than those later in the list. Therefore, how citations are ordered could influence which citations receive the most attention. Using a sample of 150,000 articles, we tested whether alphabetizing in-text citations biases readers into citing more often articles with first authors whose surnames begin with letters early in the alphabet. We found that surnames earlier in the alphabet were cited more often than those later in the alphabet when journals ordered citations alphabetically compared with chronologically or numerically. This effect seemed to be stronger in psychology journals (which have a culture of alphabetizing citations) compared with biology or geoscience journals (which primarily order chronologically or numerically) and was strongest among moderately and highly cited articles. Therefore, alphabetizing in-text citations biases citation decisions toward authors with surnames occurring early in the alphabet. These citation decisions result from an interaction between cognitive biases (more attention devoted to items earlier in a list) and the structure of the citation environment (the style in which citations are ordered). We suggest that journals using alphabetically ordered citations switch to chronological ordering to minimize this arbitrary alphabetical citation bias.

stevens_duque_2019_SM.pdf (1210 kB)
Supplementary analyses, figures, and tables

stevens_duque_2019_data.csv (9693 kB)
Data

stevens_duque_2019_rcode.R (48 kB)
R code

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