Use of Benford's law on academic publishing networks

Aleksandar Tošić and Jernej Vičič

Journal of Informetrics, 2021, vol. 15, issue 3

Abstract: Benford's law, also known as the first-digit law, has been widely used to test for anomalies in various data ranging from accounting fraud detection, stock prices, and house prices to electricity bills, population numbers, and death rates. Scientific collaboration graphs have been studied extensively as data availability increased. Most research was oriented towards analysing patterns and typologies of citation graphs and co-authorship graphs. Most countries group publications into categories in an attempt to objectively measure research output. However, the scientific community is complex and heterogeneous. Additionally, scientific fields may have different publishing cultures, which make creating a unified metric for evaluating research output problematic. In complex systems like these, it is important to regularly observe potential anomalies and examine them more carefully in an attempt to either improve the evaluation model or find potential loopholes and misuses. In this paper, we examine the potential application of Benford's law on the official research database of Slovenia. We provide evidence that metrics such as number of papers per researcher conform to Benford's distribution, while the number of authors per paper does not. Additionally, we observe some anomalies and provide potential reasoning behind them.

Keywords: Benford's law; Citation network; Bibliography (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:15:y:2021:i:3:s1751157721000341

DOI: 10.1016/j.joi.2021.101163

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