Patterns of authors contribution in scientific manuscripts
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Abstract (arXiv)
Science is becoming increasingly more interdisciplinary, giving rise to more diversity in the areas of expertise within research labs and groups. This also have brought changes to the role researchers in scientific works. As a consequence, multi-authored scientific papers have now became a norm for high quality research. Unfortunately, such a phenomenon induces bias to existing metrics employed to evaluate the productivity and success of researchers. While some metrics were adapted to account for the rank of authors in a paper, many journals are now requiring a description of the specific roles of each author in a publication. Surprisingly, the investigation of the relationship between the rank of authors and their contributions has been limited to a few studies. By analyzing such kind of data, here we 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 follows three general patterns according to the nature of their contributions, such as writing, data analysis, and the conduction of experiments. This was accomplished by collecting and analyzing the data retrieved from PLoS ONE and by devising an entropy-based measurement to quantify the effective number of authors in a paper according to their contributions. The analysis of such patterns confirms that some aspects of the author ranking are in accordance with the expected convention, such as the fact that the first and last authors are more likely to contribute more in a scientific work. Conversely, such analysis also revealed that authors in the intermediary positions of the rank contribute more in certain specific roles, such as the task of collecting data. This indicates that the an unbiased evaluation of researchers must take into account the distinct types of scientific contributions.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Sep 2016.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 4; 2026: 1.
8 papers.
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- 2026SurveyAgent-HKA: A multi-agent framework for scientific survey generation with LLMs and human knowledge augmentation5 Sep 2026
- 2025SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Models25 Aug 2025
- 2025Leveraging GANs for citation intent classification and its impact on citation network analysis27 May 2025
- 2025Examining Linguistic Shifts in Academic Writing Before and After the Launch of ChatGPT: A Study on Preprint Papers18 May 2025
- 2025Graph machine learning for flight delay prediction due to holding manouver6 Feb 2025
- 2023Chain-of-Factors Paper-Reviewer Matching23 Oct 2023
- 2022Recovering network topology and dynamics via sequence characterization30 Jun 2022
- 2021On predicting research grants productivity20 Jun 2021