I am new to the field of academia, and when performing a literature review for really any topic, I am puzzled as to why some papers have so many co-authors.

Most papers have only about 1-5 authors which I can understand but I can't seem to understand how 10-20 people could all meaningfully contribute to a single paper. How possible is it that co-authorship is being gifted?

Are there any reasons why so many co-authors could be justified?

Update 11/11/19: Some comments have suggested this question may be a duplicate. To clarify: I was not referring to large-scale taskforces that produce world-changing results such as the Higgs Boson project (What is the point of listing 1000 authors for a single scientific paper?). Those projects clearly play by different rules. I was meaning routine contributions to journals (such as a new formula or algorithm) where I struggle to understand how so many people could all meaningfully contribute to a small (albeit important) idea.

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    What field are you talking about? – scaaahu Nov 7 '19 at 7:40
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    In mathematics, polymath projects are quite successful and have many authors. See en.wikipedia.org/wiki/Polymath_Project – Prof. Santa Claus Nov 7 '19 at 9:11
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    Seems to have been answered here: academia.stackexchange.com/questions/63440/… – stackzebra Nov 7 '19 at 19:25
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    I'm on some papers with more than >500 contributers. All these belong to a collaboration of a particle physics experiment. Designing the machine, creating the machine, setting up the machine, analzying and predicting data, formulating mathematical and physical models. This single experiment started in the 90s and is currently build up. And the amount of researches grow over time, for sure. Authors of papers are all who are part of the collaboration when the paper is submitted and when the machine is running and gathering data, all former researches for the first three years. – Ben Nov 8 '19 at 6:08
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    I don't think this question is a duplicate. As explained in my answer, there are distinct cases of 10-20 author papers which don't apply to 1000 author papers and that do not include industry authors. – lighthouse keeper Nov 8 '19 at 14:03

In my field, where author numbers between one and six are the norm, reasons for having more include the following:

  • The paper results from a large-scale collaboration between different groups that developed different parts of the overall work.
  • The paper is supposed to give a broad picture overview of something, like in the case of a survey paper or a research roadmap paper. The authors are experts for the different considered areas.
  • The paper results from a collaborative brainstorming effort. Such papers are sometimes written by the participants of a research meeting (like the famous Dagstuhl seminars), or a breakout group from such.
  • The paper results from a student project, and most of the co-authors are actually students.
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    This is all accurate, but I think the answer would be improved by fleshing out the "large-scale collaboration". Some experimental work, especially in physics, can involve many people that do specialized work as part of the experiment which are acknowledged as authors for those specialized contributions even if they did not aid in the drafting of the written document. – TimothyAWiseman Nov 7 '19 at 22:20
  • I'm right now involved in writing a manuscript about some experiments where many labs participated, and we had multiple meetings where all labs together decided/developed the details for the experimental procedure, so large-scale together with collaborative brainstorming. – cbeleites unhappy with SX Nov 9 '19 at 20:10

De facto, co-authorship means different things in different fields.

As Zenon mention in their answer, the Higgs Boson paper has 5154 authors. Does that mean that there is a first author who sent around the manuscript to all co-authors, then waited for 5153 people to give feedback and OK? No, absence of response does not hold up publication and is taken as agreement on the content. As I understand it, on this collaboration, the criterion for co-authorship were that you'd been part of the team for a year (source: personal communication).

In my field (Earth Observation), there are sometimes papers on validations or campaigns that include many different instruments. For each instrument there is a PI and their postdoc and/or PhD student, who should be on the paper even if their only contribution is "provide data". They need that to prove to their funding agencies that the data are being used for science. With 10 instruments, that can easily mean 20–30 or more co-authors.

So to answer your question: it depends. The reasons for papers to have many co-authors are field and even sub-field dependent.

See also: Academia varies more than you think it does – The Movie

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    "they need it for their funding" sounds as if they didn't deserve to be on the paper but get there because of merciful main authors and financial reasons. Contributing data is a sufficient reason on its own, you don't need to write text to contribute to a paper. Some PIs only provide ideas and proof-read their students, they still contribute, same here. – Frank Hopkins Nov 7 '19 at 17:01
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    @FrankHopkins I meant, they need the co-authorship to prove to their funding agencies that their data are being used. Will edit to clarify. – gerrit Nov 8 '19 at 12:55
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    The papers in large particle physics collaborations are circulated to the whole collaboration. But this happens in the form of a bulk email telling where to look for the draft, where to send comments, and the deadline for comments. Lack of response for any given author doesn’t hold up the process. At least one paper I’m on went through four rounds of this and a in-person collaboration meeting. – dmckee --- ex-moderator kitten Nov 9 '19 at 6:44
  • same procedure (circulating to everyone with deadline for comments/changes etc.) for manuscript with >20 coauthors I'm involved with right now (analytical/physical chemistry). – cbeleites unhappy with SX Nov 9 '19 at 20:05

There are many reasons. Science is becoming more and more collaborative, especially in fields requiring experiments. See for example the ATLAS and CMS paper on the discovery of the Higgs Boson which has 5,154 authors, or this 1000 Genome project paper which has hundreds.

Those are extreme examples, but with the increase in complexity it is often required to recruit collaborators with a large amount of complementary skills to be able to gather the data and analyze it.

There are also discussions about what really warrants authorship and how those rules are not necessarily clear. There is an interesting discussion on the blog of PLOS about that.


As others have written, this is extremely field dependent.

I work in two fields. In one (forecasting) the maximum number of coauthors has been five, including me, and that was a review paper in which everyone indeed contributed different expertise and a different view on a subfield.

In clinical psychology, I have collaborated on papers with up to ten coauthors, including me. To a certain extent, the number of coauthors was driven by different kinds of expertise. I did the statistics, other people did the fMRI analyses, yet other people the blood analyses, and the PI had the overall vision that got everything started, funded and seen through to the end. That's four people right there. Add a postdoc that supervised the day-to-day running of the project, and finally multiple people who did the psychological intervention, or psychotherapy. This is a very time-consuming effort, and you need multiple therapists to be able to process a sufficiently large number of participants, each of whom may require many one-on-one sessions. Plus, of course, all the ancillary activities like report writing for each and every participant.

Thus, one driver especially in clinical psychology is the sheer amount of work necessary to acquire each data point.


My maximum is 9 (here). It occurred on an interdisciplinary paper in Molecular Biology and Evolution.

Six from computer science:

  1. The lead author was a student in our lab. There's another student who helped him, who became coauthor.
  2. Aside from me, there are three other teachers from our lab, who probably offered advice to the students during weekly research meetings. I would guess one teacher came up with the basic ideas, and another teacher is the student's supervisor.
  3. I surely would have done much of the paper revising.

Three from biology:

  1. The professor whose biological data we use.
  2. Two of his students, who I've never met and do not know their role in the paper. I assume they helped the biology professor obtain the data.

Combining methodologies often requires a team for each, with their own PI and then a coordinating PI.

For example a paper I'm familiar with looked at fMRI and gait metrics, so there was (1) 3-4 people who worked on the fMRI data, (2) 3-4 people who worked on the gait data, (3) a large group of senior professors who wrote the original grant and coordinated the study (this was across two sites), and finally (4) the overall PI.


Consider a full length life-sciences article. It might have 8 figures, each of which might be composed of 6 panels. There will also probably be at least the same amount of supplementary material (often more) that is available from the journal's website, but not in the main text of the paper. Thats 96 figure panels. Now consider that even the most simple experiment takes at least 2 weeks, and will have to be done in at least triplicate. So, that's a minimum of 6 weeks per panel even for easy experiments, or 576 weeks worth of experiments.

A grad student in the UK gets 3 years for data collection, or 141 weeks working 47 weeks a year. So that's 4 PhDs worth of data. Then their will be multiple PIs, maybe because there are different sorts of data being collected, maybe because no one PI has that many PhD students doing nothing. There will probably be at least one, but probably more lab techs.

If there is animal work there will be an animal house tech, if there is clinical work there will be a clinical team (Doctor, Nurses, counsellors etc).

Also consider that the people who generate the data might no be the people who can analyse and model it, so there will be at least one biostatistician or bioinformatician + their PI.

Of course all this assumes that 1) everything works smoothly, nothing needs doing again and all the experiments you do are the correct ones first time and they all make it into the paper, which is frankly preposterous; and 2) That you are able to wait 3 years to get everything together - if you need it in 1.5 years then double all the numbers above.


It really depends on the field and the culture of that field. For example, I find that in several fields, most projects are run by a PI and require many student and professional researchers to gather data, perform experiments, analyze results, etc. As a result, the entire team usually ends up on the paper, even if there is a lot of variance in the amount of contribution that each member of the team brought to the paper. This is common in fields like biology, chemistry, biochemistry, psychology, and physics.

Having many coauthors is also common in fields that are interdisciplinary and straddle application and theory. For example, in statistics, you often find that there are a multiple statisticians collaborating with multiple professionals in other fields, like biology or medicine. The statisticians develop the statistical models and do the data analysis, while, say, the biologists help provide necessary scientific knowledge and expert opinion.

Another good example is when a paper began as a student research project, especially for students new to research. You often find that several students are put on the same project to make it easier on the students and provide a smoother transition into research.

A more specific example is the following. I know (by observation and word of mouth) that the culture in many computer science departments to place a lot of students on a single paper in order to pump out a lot of papers quickly. I am not sure on the exact the reason for this. But it is not unusual to find computer science PhD students with many publications, with many of those papers having several coauthors.

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