Harmonic coauthor credit: A parsimonious quantification of the byline hierarchy

Nils T. Hagen

Journal of Informetrics, 2013, vol. 7, issue 4, 784-791

Abstract: In this paper the accuracy of five current approaches to quantifying the byline hierarchy of a scientific paper is assessed by measuring the ability of each to explain the variation in a composite empirical dataset. Harmonic credit explained 97% of the variation by including information about the number of coauthors and their position in the byline. In contrast, fractional credit, which ignored the byline hierarchy by allocating equal credit to all coauthors, explained less than 40% of the variation in the empirical dataset. The nearly 60% discrepancy in explanatory power between fractional and harmonic credit was accounted for by equalizing bias associated with the omission of relevant information about differential coauthor contribution. Including an additional parameter to describe a continuum of intermediate formulas between fractional and harmonic provided a negligible or negative gain in predictive accuracy. By comparison, two parametric models from the bibliometric literature both had an explanatory capacity of approximately 80%. In conclusion, the results indicate that the harmonic formula provides a parsimonious solution to the problem of quantifying the byline hierarchy. Harmonic credit allocation also accommodates specific indications of departures from the basic byline hierarchy, such as footnoted information stating that some or all coauthors have contributed equally or indicating the presence of a senior author.

Keywords: Byline hierarchy; Coauthor credit; Harmonic formula; Bibliometric bias; Parsimony (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157713000527
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:7:y:2013:i:4:p:784-791

DOI: 10.1016/j.joi.2013.06.005

Access Statistics for this article

Journal of Informetrics is currently edited by Leo Egghe

More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().