
doi: 10.1162/qss_a_00361
Abstract This article aims to improve our understanding of scientometric data in a Benfordian context. Recently, Benford’s law has been used to detect scientific fraud. However, we need to better understand its application to scientometric data. Through the implementation of Benford’s law and the generalized Benford’s law, we propose a categorization of science products and metrics. To this end, we have performed chi-square, MAD, and Max tests on data sets from WoS and Scopus as well as on historical data. This enables us to better understand the behavior and characteristics of these objects in a Benfordian context, and invites us to discuss the nature of bibliometric indicators in this particular context.
MAX test, Generalized Benford’s law, Zipf’s law, Scientometrics, [INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR], MAD (Mean Absolute Deviation), [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], Benford’s law, [SHS.INFO] Humanities and Social Sciences/Library and information sciences
MAX test, Generalized Benford’s law, Zipf’s law, Scientometrics, [INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR], MAD (Mean Absolute Deviation), [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], Benford’s law, [SHS.INFO] Humanities and Social Sciences/Library and information sciences
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
