research paper with highest number of authors

Most authors on a single peer-reviewed academic paper

The most authors on a single peer-reviewed academic paper is 15,025 and was achieved by the COVIDSurg and GlobalSurg Collaboratives at the University of Birmingham and the University of Edinburgh in the UK, as verified on 24 March 2021.

Authors from across 116 countries collaborated on this academic paper. Data was urgently needed to inform decision making and improve safety for patients undergoing surgery during the pandemic.

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How Many Number of Authors Can Be There in a Research Paper?

In the intricate tapestry of scientific exploration, the question of authorship weaves a narrative of collaboration, expertise, and ethical considerations. As research endeavours become increasingly interdisciplinary and collaborative, the dynamics of authorship in academic papers have evolved.

In this blog post, we delve into the fascinating realm of authorship – exploring the factors that influence the number of authors in a research paper, deciphering the collaboration dynamics that shape these decisions, and navigating the ethical considerations that underpin the authorship landscape.

Join us on this exploration of the intricacies surrounding authorship in the academic world, where each contributor plays a unique role in advancing the frontiers of knowledge.

Introduction

Factors influencing authorship, collaboration dynamics, whether number of authors has any influence on citation count, the physics paper with highest number of 5,000+ authors.

In the realm of academic research, the authorship of a paper serves as a testament to the collaborative efforts and intellectual contributions that culminate in the creation of knowledge. Authorship goes beyond a mere listing of names; it reflects the varied roles, expertise, and collaboration dynamics within a research project.

Consider, for instance, a groundbreaking study in genetics that unveils a novel gene responsible for a rare disease. In this scenario, the research team might comprise geneticists, bioinformaticians, clinicians, and statisticians, each bringing their unique expertise to the table. The authorship of the resulting research paper becomes a crucial aspect in acknowledging and recognizing the distinct contributions made by each team member.

The number of authors for a research paper is determined by the collaborative nature of the study, the diversity of expertise required, and adherence to disciplinary norms, with no strict limit but a reflection of individual contributions and collaboration dynamics.

Understanding the dynamics behind the number of authors is akin to unravelling the narrative of scientific collaboration. A single-author paper might suggest an individual’s comprehensive work in a specific niche, while a multi-authored paper can signify the synergy of minds pooling their skills and knowledge to address complex, multifaceted research questions.

As we embark on this exploration of authorship in research papers, it’s essential to recognize that the number of authors is not merely a logistical detail but a reflection of the intricate interplay of skills, ideas, and contributions within the scientific community. Join us as we unravel the layers of authorship, understanding its nuances and the evolving landscape that shapes the way we attribute credit in the world of academia.

In the vast landscape of academic research, the number of authors on a paper is influenced by a myriad of factors that extend beyond the mere act of writing. Understanding these factors is crucial for researchers, institutions, and readers alike.

A. Nature of the Research: Collaborative vs. Individual Work

In collaborative research endeavours, the complexity and scope of the project often necessitate a team of individuals with diverse skills. Take, for example, a large-scale environmental study aiming to understand the impact of climate change on a particular ecosystem. Scientists, statisticians, field researchers, and data analysts may all contribute substantially to different facets of the project. The resulting research paper becomes a collective effort, showcasing the synergy of expertise that goes beyond what a single researcher could achieve.

On the other hand, individual research projects, particularly in certain theoretical or experimental domains, may see a sole author taking the lead. For instance, a mathematician exploring a novel theorem or a laboratory researcher conducting a highly specialized experiment might find themselves as the sole author, reflecting the self-sufficiency and independence of their work.

B. Role of Contribution and Expertise in Determining Authorship

Authorship isn’t just about being part of the team; it’s about making significant intellectual contributions. Consider a medical study investigating a new treatment for a specific condition. The clinicians involved might provide valuable insights into patient outcomes, while statisticians contribute their expertise in data analysis. The project lead may contribute not only by designing the study but also by synthesizing findings into a coherent narrative. The determination of authorship, in this case, is guided by the distinctive contributions of each team member.

C. Variations Based on Academic Disciplines and Research Practices

Different academic disciplines and research practices may have varying norms regarding authorship. In fields like physics or astronomy, it’s common to see long lists of authors due to collaborative efforts on large-scale projects, such as experiments at particle accelerators or telescope observations. In contrast, some social sciences or humanities disciplines may place more emphasis on individual authorship.

Understanding these variations is vital for researchers navigating the authorship landscape. It requires an awareness of disciplinary norms, effective communication within research teams, and a commitment to recognizing and valuing diverse contributions.

As we delve into the complexities of authorship, it becomes evident that it’s not a one-size-fits-all concept; rather, it’s a nuanced interplay of factors that shape the credit attributed to individuals in the academic tapestry.

Collaboration is the heartbeat of scientific progress, fueling the generation of new ideas and the pursuit of knowledge. The dynamics of collaboration significantly influence the number of authors in a research paper, reflecting the collective nature of scientific exploration.

A. Impact of Collaboration on Authorship

In collaborative research endeavours, the number of authors is intricately linked to the complexity and scale of the project. Consider a scenario where researchers from diverse backgrounds join forces to study the impact of artificial intelligence on healthcare. This multidisciplinary collaboration may involve computer scientists, medical professionals, statisticians, and ethicists, each contributing their unique expertise. In such cases, the resulting research paper becomes a tapestry woven with the threads of collective insights, leading to a higher number of authors.

B. Collaborative Efforts within Research Teams

Research teams, whether in academia or industry, are often engines of innovation. The collaborative efforts within these teams can range from experimental work in a laboratory to large-scale data analysis projects. For instance, a team of geneticists working on decoding the genome of a rare species might include experts in molecular biology, bioinformatics, and ecology. The collaborative nature of the project, with each team member bringing specialized knowledge, contributes to the richness of the research and may result in a higher number of authors.

C. Interdisciplinary Projects and Authorship

Interdisciplinary projects, where researchers from different fields converge to address complex challenges, are becoming increasingly common. Imagine a project aiming to develop sustainable solutions for urban planning, involving urban designers, environmental scientists, economists, and sociologists. The amalgamation of diverse perspectives often leads to a collective authorship structure, where each discipline’s contribution is acknowledged. Interdisciplinary projects showcase the strength of collaboration in tackling multifaceted issues, reflected in the comprehensive authorship lists.

Understanding collaboration dynamics is pivotal for researchers navigating the modern scientific landscape. It involves not only recognizing the value of diverse expertise but also effectively communicating and coordinating efforts within a team. The resulting research papers become artefacts of collective intelligence, highlighting the interconnected web of collaborations that drive the advancement of knowledge.

The number of authors on a research paper is generally not directly influenced by the citation count . Authorship decisions are more closely tied to the contributions and roles of individuals in the research project rather than the subsequent impact or recognition garnered by the paper.

The number of citations a paper receives is often considered a measure of its impact and influence within the scholarly community. Papers with more citations are generally viewed as having made a more significant contribution to the field. However, this citation count typically becomes apparent after the paper is published, and authorship decisions are made during the preparation and submission phases.

That said, there can be indirect connections. Highly impactful papers may result from extensive collaborative efforts, involving multiple authors. In such cases, a paper’s influence (reflected in citation count) and the number of authors might both be indicative of the scale and importance of the research.

In summary, while citation count is a post-publication metric that reflects the impact of a paper, the decision on the number of authors is typically influenced by factors such as the nature of the research, individual contributions, and collaborative dynamics, rather than the anticipated impact of the paper.

I have written articles on ” Step by step guide on Research Paper Citation ” and “ How to increase the citation count of your research paper? “. Please visit the articles for more details.

A groundbreaking physics paper published in Physical Review Letters has set a record with an astonishing 5,154 authors , making it one of the largest collaborative efforts in scientific literature. The 33-page article, primarily focused on the research involving the Large Hadron Collider (LHC) at CERN, details the collaboration between two detector teams, ATLAS and CMS. This joint effort allowed for a more precise estimate of the mass of the Higgs boson, narrowing it down to ±0.25%.

Published on May 14, the paper faces the unique challenge of devoting only the initial nine pages to the research, while the subsequent 24 pages list the extensive number of authors and their affiliated institutions. The collaboration involved scientists and engineers from diverse backgrounds and numerous countries, illustrating the global scale of modern scientific endeavors.

The record-breaking author list presented challenges in merging the styles of the two collaborating teams, but the resulting paper showcases an impressive level of cooperation in responding to editorial and referee comments. While the physics community is accustomed to the concept of “hyper authorship,” with previous papers exceeding 3,000 authors, this particular article stands out for its remarkable scale and the complexity of coordinating contributions from thousands of individuals. The achievement underscores the collaborative nature of large-scale experimental physics and the dedication of researchers in pushing the boundaries of our understanding of the universe.

You may have having few more questions in your mind. For example, you may be wondering “ Whether Author’s position in a research paper matters? “, “ What are the consequences of plagiarism? “, “ How to identify good Journals for my research papers? “, “ How to avoid predatory conferences and Journals while applying for your paper? ” Please click the links with the keywords which I have listed in this paragraph for detailed information on those topics.

In the ever-evolving landscape of academic research, the question of how many authors should be credited on a paper is not a mere logistical consideration but a reflection of the intricate web of collaboration, expertise, and disciplinary norms. As we’ve explored the factors influencing authorship, it becomes evident that the number of authors is a dynamic aspect of scientific communication.

In essence, the number of authors on a research paper is not a mere statistic but a reflection of the collaborative spirit inherent in the pursuit of knowledge. It’s a testament to the diversity of voices, perspectives, and skills that come together to advance our understanding of the world. The future of research lies in fostering effective collaborations, appreciating individual contributions, and collectively pushing the boundaries of human knowledge.

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Divide and concur: A physics paper with 5,154 authors

A physics paper with 5,154 authors is the newest reached pinnacle in people’s drive to divide and concur, when there’s credit to be had. Those 5,154 physicists stand a-write on the collective shoulders of the 976 physicians who shared the 1993 Ig Nobel Prize for literature .

The new, 5,154 physicist paper is: “ Combined Measurement of the Higgs Boson Mass in pp Collisions at √ s = 7 and 8 TeV with the ATLAS and CMS Experiments ,” G. Aad et al . [5,154 authors total] (ATLAS Collaboration), (CMS Collaboration), Physical Review Letters , 114, 191803, published 14 May 2015.

Davide Castelvecci, writing solo in Nature News , gives an appreciation of the 5,154 :

Physics paper sets record with more than 5,000 authors Detector teams at the Large Hadron Collider collaborated for a more precise estimate of the size of the Higgs boson. A physics paper with 5,154 authors has — as far as anyone knows — broken the record for the largest number of contributors to a single research article. Only the first nine pages in the 33-page article, published on 14 May in Physical Review Letters , describe the research itself — including references. The other 24 pages list the authors and their institutions. The article is the first joint paper from the two teams that operate ATLAS and CMS, two massive detectors at the Large Hadron Collider (LHC) at CERN , Europe’s particle-physics lab near Geneva, Switzerland. Each team is a sprawling collaboration involving researchers from dozens of institutions and countries….

Here is the beginning of the new paper’s list of 5,154 co-authors, most of whom are still alive [according to the paper itself, not all of them are]:

BONUS: A fun calculation for you to perform with friends: How many minutes it would that take to read aloud the complete list of 5,154 co-authors ?

BONUS: Another report in Nature News , published two days earlier than “Physics paper sets record with more than 5,000 authors”): “ Fruit-fly paper has 1,000 authors “

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Google Scholar Metrics

Google Scholar Metrics provide an easy way for authors to quickly gauge the visibility and influence of recent articles in scholarly publications. Scholar Metrics summarize recent citations to many publications, to help authors as they consider where to publish their new research.

To get started, you can browse the top 100 publications in several languages , ordered by their five-year h-index and h-median metrics. To see which articles in a publication were cited the most and who cited them, click on its h-index number to view the articles as well as the citations underlying the metrics.

You can also explore publications in research areas of your interest. To browse publications in a broad area of research, select one of the areas in the left column. For example: Engineering & Computer Science or Health & Medical Sciences .

To explore specific research areas, select one of the broad areas, click on the "Subcategories" link and then select one of the options. For example: Databases & Information Systems or Development Economics.

Browsing by research area is, as yet, available only for English publications. You can, of course, search for specific publications in all languages by words in their titles.

Scholar Metrics are currently based on our index as it was in July 2023 .

Available Metrics

The h-index of a publication is the largest number h such that at least h articles in that publication were cited at least h times each. For example, a publication with five articles cited by, respectively, 17, 9, 6, 3, and 2, has the h-index of 3.

The h-core of a publication is a set of top cited h articles from the publication. These are the articles that the h-index is based on. For example, the publication above has the h-core with three articles, those cited by 17, 9, and 6.

The h-median of a publication is the median of the citation counts in its h-core. For example, the h-median of the publication above is 9. The h-median is a measure of the distribution of citations to the articles in the h-core.

Finally, the h5-index , h5-core , and h5-median of a publication are, respectively, the h-index, h-core, and h-median of only those of its articles that were published in the last five complete calendar years.

We display the h5-index and the h5-median for each included publication. We also display an entire h5-core of its articles, along with their citation counts, so that you can see which articles contribute to the h5-index. And there's more! Click on the citation count for any article in the h5-core to see who cited it.

Coverage of Publications

Scholar Metrics currently cover articles published between 2018 and 2022 , both inclusive. The metrics are based on citations from all articles that were indexed in Google Scholar in July 2023 . This also includes citations from articles that are not themselves covered by Scholar Metrics.

Since Google Scholar indexes articles from a large number of websites, we can't always tell in which journal a particular article has been published. To avoid misidentification of publications, we have included only the following items:

• journal articles from websites that follow our inclusion guidelines ;
• selected conference articles in Engineering and Computer Science.

Furthermore, we have specifically excluded the following items:

• court opinions, patents, books, and dissertations;
• publications with fewer than 100 articles published between 2018 and 2022;
• publications that received no citations to articles published between 2018 and 2022.

Overall, Scholar Metrics cover a substantial fraction of scholarly articles published in the last five years. However, they don't currently cover a large number of articles from smaller publications.

Inclusion and Corrections

If you can't find the journal you're looking for, try searching by its abbreviated title or alternate title. There're sometimes several ways to refer to the same publication. (Fun fact: we've seen 959 ways to refer to PNAS.)

If you're wondering why your journal is not included, or why it has fewer citations than it surely deserves, that is often a matter of configuring your website for indexing in Google Scholar. Please refer to the inclusion manual . Also, keep in mind that Scholar Metrics only include publications with at least a hundred articles in the last five years.

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Does the Number of Authors Matter? Data from 101,580 Research Papers

I analyzed a random sample of 101,580 full-text research papers, uploaded to PubMed Central between the years 2016 and 2021, in order to explore the influence of the number of authors of a research paper on its quality.

I used the BioC API to download the data (see the References section below).

Here’s a summary of the key findings

1. The median research paper had 6 authors, with 90% of papers having between 1 and 15 authors .

2. The median number of authors of a research paper increased, from 3 to 6, in the past 20 years . The data also show that single-authored papers are becoming less popular , as the percentage of single-authored papers dropped from 33.9% in 2002 to 2.1% in 2021.

3. Descriptive studies (such as case reports, case series, and cross-sectional studies) usually require less work and therefore have fewer authors than analytical studies (such as cohort, case-control, and experimental studies) .

4. The number of authors does not influence the quality of the journal in which the research paper is published . In fact, the median single-authored paper is published in a journal with an impact factor of 3.11 compared to 3.15 for the median multiple-authored paper.

5. Single-authored research papers receive 34.7% less yearly citations compared to multiple-authored papers (p < 0.01).

1. How many authors can a research paper have?

The following is a histogram representing the distribution of the number of authors:

The graph shows that:

• The distribution of authors has a right skew, as expected.
• Most research papers have less than 10 authors.
• It is somewhat exceptional for a research paper to have more than 15 authors.

Here’s a table that summarizes these data in numbers:

In our sample of 101,580 research papers, the median research paper was written by 6 authors, and the majority had between 4 and 9 authors. Only 5% were written by single authors (n=5,280).

A physics paper had 2,902 authors, which was the largest number of contributors to a single work in our sample (here’s the link to the paper on PubMed ).

2. Number of authors: 20-year trend

The 20-year trend shows that the median number of authors increased from 3 in 2002 to 6 in 2012 and remained constant for the past decade:

Looking at the trend of single-authored papers below, we see that these are declining in popularity over the past 20 years:

Perhaps that collaborations are more encouraged nowadays, especially for larger projects.

If this is the case, then the number of authors should differ for various study designs, as different types of studies require different amount of work. So, this is what we are going to discuss next.

3. Number of authors of different article types

The following table shows the median number of authors of different article types:

The data agree with the hypothesis that descriptive studies (such as case reports, case series, and cross-sectional studies) usually require less amount of work and therefore have fewer authors — medians between 5 and 6 authors — than analytical studies (such as cohort, case-control, and experimental studies) — medians between 7 and 8 authors.

4. Number of authors of papers in different journals

To study the influence of the number of authors on the quality of the journal in which the paper is published, I used linear regression to predict the journal impact factor given the number of authors.

Here’s the outcome of that model:

The model shows that research papers with more authors are published in slightly higher-quality journals: an increase in 1 author is associated with an increase of 0.03 in the journal impact factor. Although statistically significant, this effect is practically negligible.

In addition, when comparing the median journal impact factor for single-authored and multiple-authored research papers, I found only a difference of 0.04 (3.11 and 3.15, respectively)

5. Does the number of authors influence the citation count?

In order to study the influence of the number of authors of a paper on the number of citations it receives, I used Poisson regression to model the number of citations per year given the number of authors.

The model shows that research papers that have 1 additional author are associated with a 0.62% increase in the yearly citation count. For the median article, this means an increase of 1 citation every 100 years — with is negligible.

However, when we compare single-authored with multiple-authored papers, the Poisson model shows that the yearly citation count for single-authored papers is 34.7% less compared to multiple-authored papers (p < 0.01). Specifically, the median number of yearly citations for single-authored papers was 1.4 compared to 2.2 for multiple-authored papers.

• Comeau DC, Wei CH, Islamaj Doğan R, and Lu Z. PMC text mining subset in BioC: about 3 million full text articles and growing,  Bioinformatics , btz070, 2019.

Further reading

• Paragraph Length: Data from 9,830 Research Papers
• Can a Research Title Be a Question? Real-World Examples
• How Long Should a Research Paper Be? Data from 61,519 Examples
• How Many References to Cite? Based on 96,685 Research Papers
• How Old Should References Be? Based on 3,823,919 Examples

Long lists are eroding the value of being a scientific author

Lecturer in Library Science , City, University of London

Disclosure statement

Ernesto Priego does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

City, University of London provides funding as a founding partner of The Conversation UK.

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This month, a scientific paper by teams working at the Large Hadron Collider at CERN set the record for the number of authors on a paper – with more than 5,000 contributors . In the same week, a genomics paper had more than 1,000 authors .

The trend of increasingly long author lists on research papers is clearly getting out of hand. In addition to being impractical, it is also threatening to the entire system in which academic work is rewarded. Radical reform is needed. One way forward could be to completely remove authors on papers and replace them with project names.

Publications pay

Scientific publications have traditionally been the pinnacle of success in academia. Arguably, they are the main vehicle for academics to communicate their research to each other and, ideally, the world. Decisions about hiring – and academic career progression – are also still judged largely on an academic’s publication record.

However, these days research papers are increasingly collaborative and multiple authors are the norm in many fields. A big number of authors can boost the reach, readership and eventually citations of a paper. Many worry that long author lists can therefore be a strategy to “game” the impact of individual papers, or to exponentially increase the length of each author’s publication lists.

This will make it harder for universities and funding agencies to assess researchers based on those records. In addition, if the same rules for assessment are used across fields, this can leave fields where single authors or smaller teams are still the norm at a disadvantage. For this reason, we need to fundamentally rethink the concept of authorship, especially when it comes to large-scale collaborations.

The shift towards multiple authors has been going on for some time – especially for LHC research. Over the last decade, two published experiments from the LHC also had the highest number of authors in papers indexed by Thomson Reuters. In 2010, an ATLAS paper counted 3,221 authors, and a 2008 CMS paper listed 3,101 author names .

This rise of multiple authors in academic research papers has been dubbed “ hyperauthorship ”, and is seen in biomedicine as well as in high-energy physics. Information scientist Blaise Cronin , who coined the term, argued that while this is a common problem across many disciplines, attitudes to the trend vary across fields. For example, publishing in high-energy physics is mostly conducted by very large teams spanning several institutions and even countries. It does often make sense to have a large number of authors, and researchers are often comfortable with it.

In biomedicine, however, there is more concern about the possibility of fraudulent practice, especially the addition of people as authors who have done no work on the project. There is also concern about data integrity and quality control when so many hands have been at work in creating single paper. But both fields struggle with how best to provide credit when co-authorship is counted not only in the dozens, but the hundreds and the thousands.

Meanwhile, to a humanities scholar, the hyperauthorship at the scale seen in high-energy physics seems completely alien. But even in the humanities , an increasing reliance on data is leading to more collaboration and less work by lone scholars.

The fact that so many people are surprised every time a new paper breaks the record for number of authors just goes to show that the model we currently have might be outdated for some disciplines. Current systems for academic assessment (for example citation metrics) might give the misguided impression that the same mechanics and units of measurement can be used more-or-less uniformly across disciplines .

The alternatives

Even taking into consideration that, in some fields, thousands of authors for a single paper has been the norm for some time, it seems essential to change the way authorship is attributed. Listing students and other collaborators in the acknowledgements rather than in the author list is an alternative.

To truly leave the classical ideal of the lone scholar behind, authors involved in very large collaborations, as well as scholarly publishers, could consider leaving personal names behind to give credit instead to the collective, multi-institutional project’s name.

What is at stake is not merely a question of academic ego, but the system to reward academics based on their work. In fact, for the changes to work, the whole scholarly communications, dissemination and reward system needs to be radically renovated. As suggested by the signatories of the San Francisco Research Declaration on Research Assessment , funding bodies and universities cannot keep relying on publication lists and, in particular, citations as the main measures for academic success. Collaboration also needs to be more actively rewarded in its own right.

Hyperauthorship has transformed – and eroded – the concept of authorship having a unique value. This means that authorship cannot be taken to mean the same thing as it used to. There are no easy solutions to this problem, but embracing difference, rather than uniqueness, should be a start.

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Research impact and metrics.

• Article-level metrics

Author-level metrics

H-index and its variants, other author-level metrics, where to find your h-index, have a question.

• Journal metrics
• Responsible Use of Metrics

Author-level metrics are citation metrics  that measure the bibliometric impact  of individual authors. H-index is the best known author-level metric.  Since it was proposed by JE Hirsch in 2005 it has gained a lot of popularity amongst researchers while bibliometics scholars proposed a few variants to account for its weaknesses ( g-index , m-index are good examples).

Clarivate Analytics provides list of Highly Cited Authors .  These are individuals who, in the last 10-year period, boast the highest cumulative number of highly cited papers (papers placing in the top 1% of the distribution) for their publications across 21 broad subject categories.  The 2018 edition of Highly Cited lists slightly over 6,078 authors.   Essential Science Indicators  are a great tool in identifying authors with in the last 10 years received enough citations, in their respective disciplines, to place them in the top 1% of all authors in Web of Science.

Other metrics originally developed for academic journals  can be reported at researcher level:  author-level eigenfactor   and the author impact factor (AIF)  are such examples.  

The  h-index attempts to measure both the productivity and impact of the published work of a scientist or scholar.  The calculation was suggested by an American physicist JE Hirsch and it can be summed up as:

A scientist has an index h if h of his/her Np papers has at least h citations each, and the other (Np h) papers have no more than h citations each .

In other words, to have an h-index of 5, an author has to have 5 publications, each receiving at least 5 citations.

The criticisms of the h-index include the fact that it does not account for highly cited papers (your h-index is the same whether you most highly cited paper has a 100 or 10 citations.  Another criticism is that it does not account for the career span of the author - because it is a simple function of productivity and impact, authors with longer career spans (and more publications will always have higher scores).To help with these weaknesses h-index variants had been proposed.

g-index is a variant of the h-index that, in its calculation, gives credit for the most highly cited papers in a data set.  In the words of Leo Egghe, its inventor: " Highly cited papers are, of course, important for the determination of the value h of the h-index. But once a paper is selected to belong to the top h papers, this paper is not “used” any more in the determination of h, as a variable over time. Indeed, once a paper is selected to the top group, the h-index calculated in subsequent years is not at all influenced by this paper’s received citations further on: even if the paper doubles or triples its number of citations (or even more) the subsequent h-indexes are not influenced by this. "   The g-index is always the same as or higher than the h-index.

m-index  is another variant of the h-index that displays h-index per year since first publication. The h-index tends to increase with career length, and m-index can be used in situations where this is a shortcoming, such as comparing researchers within a field but with very different career lengths. The m-index inherently assumes unbroken research activity since the first publication. 

Author Impact Factor (AIF)  is the extension of the Impact Factor to authors. The AIF of an author A in year  t  is the average number of citations given by papers published in year  t  to papers published by A in a period of  Δ t  years before year  t . AIF is capable to capture trends and variations of the impact of the scientific output of scholars in time, unlike the h-index, which is a growing measure taking into account the whole career path.  For more information see:  Pan, RK;  Fortunato , S (2014).  "Author Impact Factor: Tracking the dynamics of individual scientific impact" .  Scientific Reports   4 : 4880.

Author-level Eigenfactor  is an attempt to use Eigenfactor methodology (originally developed to rank journals), to create a ranking list of authors in SSRN.  For description of the study and list of ranked authors see:   West, JD; Jensen, MC; Dandrea, RJ; Gordon, GJ; Bergstrom, CT. (2013). " Author-level Eigenfactor metrics: Evaluating the influence of authors, institutions, and countries within the social science research network community ".  Journal of the American Society for Information Science and Technology   64  (4): 787–801. 

There are a number of sources where you can find your h-index.  Please note that the value of the index may vary depending on the source of information (number of indexed publications, time span, etc.)  For instance, h-index derived from Google Scholar tend to be higher than that based on Web of Science or SCOPUS data.  

In Web of Science you can see a calculated h-index for a group of publications (i.e. all publications by an author) through its author search.  You can Search by author's name or enter author's ORCID or ResearcherID identifier (if known).

SCOPUS has an "author search" form allowing for searching for author names, ORCID and SCOPUS identifiers and institutional affiliations.  The return page is an author summary page with a number of author information including h-index.  

Google Scholar is another source of h-index information.  It requires creation of Google Scholar profile before providing metrics.  Refer to our LibGuide on research impact to learn to how create Google Scholar Profile .   

Publish or Perish is a freely accessible software program that retrieves and analyzes academic citations. It uses Google Scholar to obtain the raw citations, then analyzes these and presents the following associated metrics:

• Total number of papers and total number of citations
• Average citations per paper, citations per author, papers per author, and citations per year
• Hirsch's h-index and related parameters
• Egghe's g-index (g-index)
• The contemporary h-index (m-index)
• The average annual increase in the individual h-index
• The age-weighted citation rate
• An analysis of the number of authors per paper.

Contact Bibliometric Services at ULS

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• Last Updated: Mar 7, 2024 10:11 AM
• URL: https://pitt.libguides.com/bibliometricIndicators

Research contribution pattern analysis of multinational authorship papers

• Published: 10 February 2022
• Volume 127 , pages 1783–1800, ( 2022 )

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• Hsuan-I Liu 1 &
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Most research evaluations in the past adopted simple counting method to calculate the number of collaborative countries within a paper, however, the information related to the author is either neglected or excluded. Therefore, this study takes the “author” as the unit of analysis to conduct a country-level research evaluation, which mainly focus on the global publishing trend of multinational authorship papers, and their research contribution patterns that derived from the transformation of author roles. It also compares the citation impact of the four contribution patterns between China and the United States. The findings revealed that multinational authorship has become a growing trend, and China had the highest number of multinational authorship papers among all the studied nations. As for the research contribution patterns, the numbers of the dominant and the supervisory pattern papers continue to increase, while the primary and the contributory pattern papers are gradually decreasing. However, China is different from other countries. China has a high proportion of dominant, supervisory and primary pattern papers, which suggests that China gradually plays a critical role in international scientific collaboration. Nonetheless, a high degree of dominance or leadership in scientific collaboration activities does not translate into high citation impacts. It is only until 2016 that the citation impact of China’s supervisory papers exceeded the United States, as well as the dominant and primary papers in 2018. As for the contributory papers, the performance of the United States was far ahead for the past decade.

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Acknowledgements

This work was financially supported by the Center for Research in Econometric Theory and Applications (Grant no. 109L900204) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan, and by the Ministry of Science and Technology (MOST), Taiwan, under Grant No. 109-2634-F-002-045.

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Liu, HI., Huang, MH. Research contribution pattern analysis of multinational authorship papers. Scientometrics 127 , 1783–1800 (2022). https://doi.org/10.1007/s11192-022-04277-x

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• NATURE INDEX
• 01 May 2024

Plagiarism in peer-review reports could be the ‘tip of the iceberg’

• Jackson Ryan 0

Jackson Ryan is a freelance science journalist in Sydney, Australia.

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Time pressures and a lack of confidence could be prompting reviewers to plagiarize text in their reports. Credit: Thomas Reimer/Zoonar via Alamy

Mikołaj Piniewski is a researcher to whom PhD students and collaborators turn when they need to revise or refine a manuscript. The hydrologist, at the Warsaw University of Life Sciences, has a keen eye for problems in text — a skill that came in handy last year when he encountered some suspicious writing in peer-review reports of his own paper.

Last May, when Piniewski was reading the peer-review feedback that he and his co-authors had received for a manuscript they’d submitted to an environmental-science journal, alarm bells started ringing in his head. Comments by two of the three reviewers were vague and lacked substance, so Piniewski decided to run a Google search, looking at specific phrases and quotes the reviewers had used.

To his surprise, he found the comments were identical to those that were already available on the Internet, in multiple open-access review reports from publishers such as MDPI and PLOS. “I was speechless,” says Piniewski. The revelation caused him to go back to another manuscript that he had submitted a few months earlier, and dig out the peer-review reports he received for that. He found more plagiarized text. After e-mailing several collaborators, he assembled a team to dig deeper.

Meet this super-spotter of duplicated images in science papers

The team published the results of its investigation in Scientometrics in February 1 , examining dozens of cases of apparent plagiarism in peer-review reports, identifying the use of identical phrases across reports prepared for 19 journals. The team discovered exact quotes duplicated across 50 publications, saying that the findings are just “the tip of the iceberg” when it comes to misconduct in the peer-review system.

Dorothy Bishop, a former neuroscientist at the University of Oxford, UK, who has turned her attention to investigating research misconduct, was “favourably impressed” by the team’s analysis. “I felt the way they approached it was quite useful and might be a guide for other people trying to pin this stuff down,” she says.

Peer review under review

Piniewski and his colleagues conducted three analyses. First, they uploaded five peer-review reports from the two manuscripts that his laboratory had submitted to a rudimentary online plagiarism-detection tool . The reports had 44–100% similarity to previously published online content. Links were provided to the sources in which duplications were found.

The researchers drilled down further. They broke one of the suspicious peer-review reports down to fragments of one to three sentences each and searched for them on Google. In seconds, the search engine returned a number of hits: the exact phrases appeared in 22 open peer-review reports, published between 2021 and 2023.

The final analysis provided the most worrying results. They took a single quote — 43 words long and featuring multiple language errors, including incorrect capitalization — and pasted it into Google. The search revealed that the quote, or variants of it, had been used in 50 peer-review reports.

Predominantly, these reports were from journals published by MDPI, PLOS and Elsevier, and the team found that the amount of duplication increased year-on-year between 2021 and 2023. Whether this is because of an increase in the number of open-access peer-review reports during this time or an indication of a growing problem is unclear — but Piniewski thinks that it could be a little bit of both.

Why would a peer reviewer use plagiarized text in their report? The team says that some might be attempting to save time , whereas others could be motivated by a lack of confidence in their writing ability, for example, if they aren’t fluent in English.

The team notes that there are instances that might not represent misconduct. “A tolerable rephrasing of your own words from a different review? I think that’s fine,” says Piniewski. “But I imagine that most of these cases we found are actually something else.”

The source of the problem

Duplication and manipulation of peer-review reports is not a new phenomenon. “I think it’s now increasingly recognized that the manipulation of the peer-review process, which was recognized around 2010, was probably an indication of paper mills operating at that point,” says Jennifer Byrne, director of biobanking at New South Wales Health in Sydney, Australia, who also studies research integrity in scientific literature.

Paper mills — organizations that churn out fake research papers and sell authorships to turn a profit — have been known to tamper with reviews to push manuscripts through to publication, says Byrne.

The fight against fake-paper factories that churn out sham science

However, when Bishop looked at Piniewski’s case, she could not find any overt evidence of paper-mill activity. Rather, she suspects that journal editors might be involved in cases of peer-review-report duplication and suggests studying the track records of those who’ve allowed inadequate or plagiarized reports to proliferate.

Piniewski’s team is also concerned about the rise of duplications as generative artificial intelligence (AI) becomes easier to access . Although his team didn’t look for signs of AI use, its ability to quickly ingest and rephrase large swathes of text is seen as an emerging issue.

A preprint posted in March 2 showed evidence of researchers using AI chatbots to assist with peer review, identifying specific adjectives that could be hallmarks of AI-written text in peer-review reports .

Bishop isn’t as concerned as Piniewski about AI-generated reports, saying that it’s easy to distinguish between AI-generated text and legitimate reviewer commentary. “The beautiful thing about peer review,” she says, is that it is “one thing you couldn’t do a credible job with AI”.

Preventing plagiarism

Publishers seem to be taking action. Bethany Baker, a media-relations manager at PLOS, who is based in Cambridge, UK, told Nature Index that the PLOS Publication Ethics team “is investigating the concerns raised in the Scientometrics article about potential plagiarism in peer reviews”.

How big is science’s fake-paper problem?

An Elsevier representative told Nature Index that the publisher “can confirm that this matter has been brought to our attention and we are conducting an investigation”.

In a statement, the MDPI Research Integrity and Publication Ethics Team said that it has been made aware of potential misconduct by reviewers in its journals and is “actively addressing and investigating this issue”. It did not confirm whether this was related to the Scientometrics article.

One proposed solution to the problem is ensuring that all submitted reviews are checked using plagiarism-detection software. In 2022, exploratory work by Adam Day, a data scientist at Sage Publications, based in Thousand Oaks, California, identified duplicated text in peer-review reports that might be suggestive of paper-mill activity. Day offered a similar solution of using anti-plagiarism software , such as Turnitin.

Piniewski expects the problem to get worse in the coming years, but he hasn’t received any unusual peer-review reports since those that originally sparked his research. Still, he says that he’s now even more vigilant. “If something unusual occurs, I will spot it.”

doi: https://doi.org/10.1038/d41586-024-01312-0

Piniewski, M., Jarić, I., Koutsoyiannis, D. & Kundzewicz, Z. W. Scientometrics https://doi.org/10.1007/s11192-024-04960-1 (2024).

Article   Google Scholar  

Liang, W. et al. Preprint at arXiv https://doi.org/10.48550/arXiv.2403.07183 (2024).

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