Hyper-authorship skews science literature impact analysis

A new Web of Science report identifies a growing number of research articles with 1,000 or more unique authors across more than 100 different countries.

The combination of many authors plus many countries is driving a complex authorship pattern that differs from more typical academic papers and leads to elevated citation rates.

Data resulting from articles with hyper-authorship – beyond 100 authors and-or 30 countries – produces such erratic, even potentially distorting outcomes, that it should be removed from analysis at a national and institutional level, the Web of Science says in a new report titled Multi-authorship and Research Analytics.

Dr Jonathan Adams, director of the Institute for Scientific Information (ISI), Web of Science Group, who is one of the co-authors of the report, said: “A small but growing number of hyper-authored research articles are driving seriously elevated citation rates and may skew any impact analysis of the scientific literature.

“In Multi-authorship and Research Analytics we recommend that: articles with more than 10 authors should be acknowledged and separately described because they will influence interpretation; and articles with hyper-authorship be treated differently with a strong argument for removing these data from all analyses at a national and institutional level.”

Across the Web of Science, the most frequent number of authors on an article is three and 95% of global output – the 14.9 million articles analysed – has 10 or fewer authors.

The most frequent number of countries on an article is one and 99% of global output has authors from five or fewer countries.

But the report found that one additional country on an article has a greater citation benefit than one additional author, and author count is linked to a slight but continuous impact rise whereas country count is linked to a steeper impact rise.

The report describes two patterns linking complex authorship with effects that increase citation rates: a general increase associated with multi-authorship (more than 10 authors and more than five countries); and more perturbing outcomes of hyper-authorship (more than 100 authors spread across more than 30 countries).

Complex authorship (many authors, many countries) has continued to rise in the past five years. The largest relative increases are associated with a marked rise in hyper-authorship.

Author and impact patterns vary between discipline, the report says. In biology, rising author and country counts are coherently linked to rising citation impact, but in clinical medicine the effect is more erratic for higher counts with higher Category Normalized Citation Impact (CNCI) up to 100 times the world average.

In chemistry there is no strong link between author count and citations; particle physics has erratically high impact values at high country counts.

The effect of multi- and hyper-authorship can be observed at country level. The effect depends on the size of a country’s domestic research base. For all countries, citation impact increases with rising authorship, but gains at higher counts are more evident and variable for smaller countries, the report says.

Every country gains citation impact through its share of the 5% of global multi-author (10 or more) articles. In small and growing research economies the average CNCI of these articles is five or more times higher than typical articles.

The report recommends that the presence, in any sample, of articles with more than 10 authors should be acknowledged and separately described because it will influence interpretation.

“Although multi-authorship leads to higher impact, this link is coherent, progressive and regular for most (but not all) discipline categories and for some fields there is little or no effect. No change needs to be made to data management or analytics in this regard,” the report says.

However, it recommends that articles with hyper-authorship, beyond 100 authors and-or 30 countries, be treated differently.

Incoherent effects

“These articles are, to put it simply, different: they have unpredictable, incoherent effects that can sometimes be very large. There is a strong argument for removing such data from all associated analyses at national as well as at institutional level,” the report says.

Hyper-authorship produces particularly different and erratic patterns across clinical medicine and particle physics. “The effects do not fit into a broader pattern, are not repeated across all disciplines and are far from consistent. The presence of such articles may be significant, even distorting, at institutional level,” the report says.

Rising author counts are not new. In 2012, writing in ISI’s Science Watch, Chris King noted that the numbers of publications indexed on Web of Science that had more than 50 authors rose from around 400 to more than 1,000 between 1998 and 2011, while the number with more than 100 authors doubled to 600 over the same period, the report says.

In 2004 the 1,000 cap was broken with a paper of 2,500 authors. The abundance of such articles continues to increase and the record is now held by a 2015 article by the ATLAS team on the Higgs Boson, with 5,153 authors at more than 500 institutional addresses, the report added.

The count of countries listed among author affiliations has similarly increased. International collaboration was relatively scarce in the 1980s but has grown rapidly: more than half of the articles attributable to any one country now have a co-author from another.

Collective responsibility

This rise in authorship counts caused some concern about what a name in an author list meant in contemporary terms: is an author any longer synonymous with a writer and where does the accountability and collective responsibility lie?

According to Blaise Cronin, writing in the Journal of the American Society for Information Science and Technology, hyper-authorship signifies a change in research nature. The major challenges of research – population studies, epidemiology, climate change, particle and space sciences – require investment in equipment, data collection, longitudinal studies and analytical processing associated with large teams.

“The lone researcher is now a less viable model for major innovation,” the report says.