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Patterns of authors contribution in scientific manuscripts

Edilson A. Corrêa , Filipi N. Silva, Luciano da F. Costa and Diego R. Amancio

Journal of Informetrics, 2017, vol. 11, issue 2, 498-510

Abstract: Science is becoming increasingly more interdisciplinary, giving rise to more diversity in the areas of expertise. In such a complex environment, the participation of authors became more specialized, hampering the task of evaluating authors according to their contributions. While some metrics were adapted to account for the order (or rank) of authors in a paper, many journals are now requiring a description of their specific roles in the publication. Surprisingly, the investigation of the relationships between credited contributions and author's rank has been limited to a few studies. Here we analyzed such a kind of data and show, quantitatively, that the regularity in the authorship contributions decreases with the number of authors in a paper. Furthermore, we found that the rank of authors and their roles in papers follow three general patterns according to the nature of their contributions: (i) the total contribution increases with author's rank; (ii) the total contribution decreases with author's rank; and (iii) the total contribution is symmetric, with most of contributions being performed by first and last authors. This was accomplished by collecting and analyzing the data retrieved from PLoS One and by devising a measurement of the effective number of authors in a paper. The analysis of such patterns confirms that some aspects of the author ranking are in accordance with the expected convention, such as the first and last authors being more likely to contribute more diversely in a scientific work. Conversely, such analysis also revealed that authors in the intermediary positions of the rank contribute more in specific roles, such as collecting data. This indicates that the an unbiased evaluation of researchers must take into account the distinct types of scientific contributions.

Keywords: Authorship contributions; Science of science; Entropy; Text mining (search for similar items in EconPapers)
Date: 2017
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