{"id":2979,"date":"2021-01-19T23:36:39","date_gmt":"2021-01-20T04:36:39","guid":{"rendered":"http:\/\/blogs.ams.org\/beyondreviews\/?p=2979"},"modified":"2021-03-14T22:08:46","modified_gmt":"2021-03-15T02:08:46","slug":"math-in-the-time-of-coronavirus","status":"publish","type":"post","link":"https:\/\/blogs.ams.org\/beyondreviews\/2021\/01\/19\/math-in-the-time-of-coronavirus\/","title":{"rendered":"Math in the time of coronavirus"},"content":{"rendered":"

While many businesses have seen significant downturns during the pandemic, several scholarly publishers have reported increases in submissions in the first part of 2020. There are various studies and articles about the phenomenon.\u00a0 Meanwhile, at Mathematical Reviews, we have not noticed any significant increase in the number of publications in mathematics during 2020.\u00a0 Note that we count publications<\/em> and the announcements and studies just mentioned are counting submissions<\/em>.\u00a0 In what follows, I look at some data about publications in mathematics in 2020, with comparisons to 2019.\u00a0 the data come from four sources: Dimensions, Web of Science, the Mathematical Reviews Database, and the arXiv.<\/p>\n

<\/p>\n

A Scholarly Kitchen post<\/a> by Christos Petrou links to announcements about exceptional growth in submissions from three publishers: SpringerNature reporting an 11% increase in submissions<\/a> in the first six months, Elsevier reporting 25% growth<\/a> for submissions to their subscription journals from January to September, and Wiley reporting a 13% increase<\/a> for their fiscal year 2020, which ended April 30, 2020.\u00a0 \u00a0The large study by Squazzoni, Bravo, Grimaldo, Garcia-Costa, Farjam, and Mehmani<\/a> looked at hundreds of thousands of submissions to Elsevier journals between February and May in the three years 2018, 2019, and 2020.\u00a0 They found that the number of submissions to all Elsevier journals in February-May 2020 increased 58% over the number of submission in the comparable four-month period in 2019.\u00a0 For health and medicine journals, the increase was 92%.\u00a0 \u00a0Their paper does not address submission rates in mathematics.\u00a0 There are also reports that men’s productivity has increased more than women’s productivity during the pandemic.\u00a0 The study by Squazzoni, et al., looked at this in detail \u2013 indeed it is their focus, finding a statistically significant negative effect on women’s submission rates in three of the four large research areas they studied.\u00a0 Curiously, in some categories in the Squazzoni, et al. study, submissions by women went up, but those increases were far outpaced by the increases in submissions by men.\u00a0 One hypothesis mentioned in the studies is that with many scientists unable to work in their laboratories, they are finding time to write papers.\u00a0 This seems plausible, and would also explain why the phenomenon is not showing up in the mathematics literature.<\/p>\n

Growth in publications in all subjects<\/h2>\n

The Scholarly Kitchen post<\/a> by Christos Petrou mentioned above analyzed publication rates using data available via the free version of Dimensions<\/a>, which is a tool for discovering and analyzing research developed by and available from Digital Science<\/a>.\u00a0 He restricted his analysis to looking only at publications from the ERA 2018 journal list<\/a>, which is a curated list from the Australian Research Council.\u00a0 Petrou considered further restrictions to publications from ERA 2018 journals that are also in the Directory of Open Access Journals (DOAJ)<\/a> and to ERA 2018 journals not<\/em> in the DOAJ.\u00a0 He also restricted to ERA 2018 journals in the Nature Index<\/a>.\u00a0 (It seems that the Nature Index journals are a proper subset of the ERA 2018 list.)\u00a0 The data I collected from Dimensions for Nature Index journals were very different from what Petrou reported.\u00a0 I don’t know why.\u00a0 In any case, I am omitting any analysis for Nature Index journals.<\/p>\n

At the time of Petrou’s blog post (November 19, 2020), the year 2020 hadn’t finished yet, so he made forecasts about how the year would finish.\u00a0 His data from Dimensions appear to have been from October 29, 2020, based on his descriptions of his low and high estimates.\u00a0 Petrou concluded that there has been an unusual growth in publications in the sciences in 2020 and that there has not been a similar growth in the arts and humanities.\u00a0 He based this on comparisons of the Compound Annual Growth Rate (CAGR) for the years 2013 to 2019 with the estimated growth rate for 2020.\u00a0 The formula for the CAGR for this period is $(1\/6)\\ln(N_{2019}\/N_{2013})$ where $N_{2019}$ is the count of publications in 2019 and $N_{2013}$ is the count of publications in 2013.\u00a0 In just about every category, the estimates are well above the CAGR.<\/p>\n

Now that the year is done, it is possible to use complete data, rather than estimates. Petrou’s estimates were generally high, which might reflect increased activity at the start of the year, followed by a slowing in the last couple of months.\u00a0 Repeating his analysis with data from the full year, one can still come to similar conclusions in most cases:\u00a0 even though the actual growth rates for 2020 were generally lower than the estimates, they were greater than the CAGR.<\/p>\n\n\n\n\n\n\n\n
<\/td>\n<\/td>\n. . . . . . . . . .% change in 2020. . . . . . . . . .<\/strong><\/td>\n<\/tr>\n
All Subjects<\/strong><\/td>\nCAGR<\/strong><\/td>\nLow est.<\/strong><\/td>\nHigh est.<\/strong><\/td>\nActual<\/strong><\/td>\n<\/tr>\n
ERA 2018<\/strong><\/td>\n3.1%<\/td>\n17%<\/td>\n26%<\/td>\n7.5%<\/td>\n<\/tr>\n
ERA 2018
\nand DOAJ<\/strong><\/td>\n		9.4%<\/td>\n16%<\/td>\n26%<\/td>\n17.5%<\/td>\n<\/tr>\n
ERA 2018
\nnot DOAJ<\/strong><\/td>\n		2.0%<\/td>\n17%<\/td>\n26%<\/td>\n5.3%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Looking at the growth rates for the last three years indicates that the growth rates for 2020 are certainly up, but they are not quite as anomalous as the comparison with the CAGR would indicate.\u00a0 The growth rates for all of the last three years are above the CAGR.\u00a0 The high growth for 2020 looks like it is part of a trend, rather than a deviation.<\/p>\n\n\n\n\n\n\n
All Subjects<\/strong><\/td>\nCAGR<\/strong><\/td>\n% change in 2018<\/strong><\/td>\n% change in 2019<\/strong><\/td>\n% change in 2020<\/strong><\/td>\n<\/tr>\n
ERA 2018<\/strong><\/td>\n3.1%<\/td>\n4.1%<\/td>\n4.6%<\/td>\n7.5%<\/td>\n<\/tr>\n
ERA 2018 and DOAJ\u00a0<\/strong><\/td>\n9.4%<\/td>\n12.2%<\/td>\n15.6%<\/td>\n17.5%<\/td>\n<\/tr>\n
ERA 2018 not DOAJ<\/strong><\/td>\n2.0%<\/td>\n2.7%<\/td>\n2.5%<\/td>\n5.3%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Graphing the counts and the growth rates for several years shows that two of the rates have been increasing for the last three years.\u00a0 The third category, ERA 2018 not DOAJ was up dramatically for 2020, but that rate has seen a lot of fluctuation since 2010.<\/p>\n

\"Graph<\/p>\n

\"Graph<\/p>\n

\"Graph<\/p>\n

Comment<\/h4>\n

I find it curious that Christos Petrou’s predictions for 2020 were so far above the actuals.\u00a0 His method seems reasonable.\u00a0 It is possible that there was a surge in the early part of the year, that died off.\u00a0 Looking at the monthly data for submissions to the arXiv and comparing the same months in 2018, 2019, and 2020, mathematics (excluding cross-listings) had a large year-to-year increase (36.6%) for June 2020.\u00a0 Physics had a large increase spread out over June and July 2020 (18.1% and 14.7%).\u00a0 Other months had much smaller year-to-year increases, or even decreases.\u00a0 Now, arXiv data represent submissions<\/em> rather than\u00a0publications<\/em>, but they provide a hint.<\/p>\n

It was pointed out by Gabor Schubert in the comments<\/a> to Petrou’s post that you can query Crossref<\/a> for publications by month using their API.\u00a0 Crossref is an official DOI Registration Agency of the International DOI Foundation and has metadata about almost every online publication.\u00a0 The publication date is provided to Crossref by the publisher.\u00a0 The analysis by Petrou was intentionally focused on a strict subset of the scholarly literature.\u00a0 The Crossref data, being from every publisher registered with Crossref, is from a much larger set.<\/p>\n

Looking at the Crossref data for journal articles for January 1 to October 31 gives:<\/p>\n\n\n\n\n\n\n\n\n
Jan to Oct<\/strong><\/td>\nCount<\/strong><\/td>\n% Change<\/strong><\/td>\n<\/tr>\n
2016<\/td>\n2,389,254<\/td>\n<\/td>\n<\/tr>\n
2017<\/td>\n2,529,461<\/td>\n5.9%<\/td>\n<\/tr>\n
2018<\/td>\n2,719,713<\/td>\n7.5%<\/td>\n<\/tr>\n
2019<\/td>\n2,932,805<\/td>\n7.8%<\/td>\n<\/tr>\n
2020<\/td>\n3,189,889<\/td>\n8.8%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Here are the Crossref counts for the full years:<\/p>\n\n\n\n\n\n\n\n\n
Jan to Dec<\/strong><\/td>\nCount<\/strong><\/td>\n% Change<\/strong><\/td>\n<\/tr>\n
2016<\/td>\n3,425,201<\/td>\n<\/td>\n<\/tr>\n
2017<\/td>\n3,607,850<\/td>\n5.3%<\/td>\n<\/tr>\n
2018<\/td>\n3,870,301<\/td>\n7.3%<\/td>\n<\/tr>\n
2019<\/td>\n4,181,142<\/td>\n8.0%<\/td>\n<\/tr>\n
2020<\/td>\n4,449,468<\/td>\n6.4%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Indeed, the growth for the whole year was much lower than what the first ten months would have predicted.<\/p>\n

Looking more closely at the Crossref data, one sees that monthly publication rates increase from January to December each year.\u00a0 Indeed, the publication rate for the second half of any of the five years 2016 to 2020 is 37% to 39% higher than the publication rate for the corresponding first half of the year.\u00a0 Publication rates in the last two months of the year tend to be about 1.8 times as high as average monthly publication rates in the same year.\u00a0 The year 2020 was an exception in that the November and December publication rates were only 1.7 times as high as the average monthly publication rates for 2020.\u00a0 In other words, it appears that Christos Petrou’s predictions for 2020 may have been thrown off by a smaller increase in November and December than usual.<\/p>\n

Growth in publications in mathematics<\/h2>\n

Dimensions data<\/h3>\n

Let’s begin by looking at a subset of the data set used by Petrou.\u00a0 Using the Dimensions data for publications just in mathematics (Field of Research = 01 Mathematical Sciences) gives noticeably different trends from the data for all subjects.<\/p>\n\n\n\n\n\n\n
Mathematics<\/strong><\/td>\nCAGR<\/strong><\/td>\n% change in 2018<\/strong><\/td>\n% change in 2019<\/strong><\/td>\n% change in 2020<\/strong><\/td>\n<\/tr>\n
ERA 2018<\/strong><\/td>\n2.3%<\/td>\n6.2%<\/td>\n7.1%<\/td>\n8.0%<\/td>\n<\/tr>\n
ERA 2018 and DOAJ\u00a0<\/strong><\/td>\n5.6%<\/td>\n25.8%<\/td>\n24.7%<\/td>\n36.8%<\/td>\n<\/tr>\n
ERA 2018 not DOAJ<\/strong><\/td>\n1.9%<\/td>\n3.9%<\/td>\n4.7%<\/td>\n3.3%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Again, it is instructive to look at graphs of the counts and growth rates since 2010.\u00a0 In each category, the growth rate for 2020 beats the CAGR, but looking at the trends in the growth rates, these do not look exceptional.<\/p>\n

\"Graphs<\/p>\n

\"Graphs<\/p>\n

\"Graphs<\/p>\n

Once again, the growth rates in the various categories for 2020 are above the CAGR, but so are the growth rates for 2018 and 2019.<\/p>\n

Web of Science data<\/h3>\n

I searched Web of Science to look for trends.\u00a0 I restricted the search to their Science Citation Index Expanded (SCI-EXPANDED) collection<\/a>, with document type = Article<\/code>, and subject area = mathematics<\/code>.\u00a0 The results are in the following table:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Year<\/strong><\/td>\nCount<\/strong><\/td>\nGrowth<\/strong>
\nrate<\/strong><\/td>\n<\/tr>\n
2010<\/td>\n48,596<\/td>\n-1.3%<\/td>\n<\/tr>\n
2011<\/td>\n51,300<\/td>\n5.6%<\/td>\n<\/tr>\n
2012<\/td>\n54,570<\/td>\n6.4%<\/td>\n<\/tr>\n
2013<\/td>\n57,428<\/td>\n5.2%<\/td>\n<\/tr>\n
2014<\/td>\n58,720<\/td>\n2.2%<\/td>\n<\/tr>\n
2015<\/td>\n58,089<\/td>\n-1.1%<\/td>\n<\/tr>\n
2016<\/td>\n57,876<\/td>\n-0.4%<\/td>\n<\/tr>\n
2017<\/td>\n60,306<\/td>\n4.2%<\/td>\n<\/tr>\n
2018<\/td>\n62,063<\/td>\n2.9%<\/td>\n<\/tr>\n
2019<\/td>\n69,585<\/td>\n12.1%<\/td>\n<\/tr>\n
2020<\/td>\n73,715<\/td>\n5.9%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The CAGR is 3.2%.\u00a0 The growth for 2020 is not particularly remarkable within the time frame.\u00a0 The exceptional year was 2019 with a 12.1% increase over 2018,\u00a0 but that growth rate was not sustained in 2020, dropping by half.\u00a0 \u00a0The graph of the counts and growth rates is below:<\/p>\n

\"Graphs<\/p>\n

For comparison, here are the data for physics<\/strong> in Web of Science.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Year<\/strong><\/td>\nCount<\/strong><\/td>\nGrowth<\/strong>
\nrate<\/strong><\/td>\n<\/tr>\n
2010<\/td>\n118,671<\/td>\n0.4%<\/td>\n<\/tr>\n
2011<\/td>\n126,177<\/td>\n6.3%<\/td>\n<\/tr>\n
2012<\/td>\n126,845<\/td>\n0.5%<\/td>\n<\/tr>\n
2013<\/td>\n132,505<\/td>\n4.5%<\/td>\n<\/tr>\n
2014<\/td>\n133,093<\/td>\n0.4%<\/td>\n<\/tr>\n
2015<\/td>\n133,948<\/td>\n0.6%<\/td>\n<\/tr>\n
2016<\/td>\n134,985<\/td>\n0.8%<\/td>\n<\/tr>\n
2017<\/td>\n136,760<\/td>\n1.3%<\/td>\n<\/tr>\n
2018<\/td>\n142,437<\/td>\n4.2%<\/td>\n<\/tr>\n
2019<\/td>\n146,906<\/td>\n3.1%<\/td>\n<\/tr>\n
2020<\/td>\n149,329<\/td>\n1.6%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\"Counts<\/h3>\n

Mathematical Reviews data<\/h3>\n

At Mathematical Reviews, we receive journal articles, conference proceedings, and books in various ways.\u00a0 Some are delivered to us electronically by the publishers.\u00a0 Some we retrieve electronically.\u00a0 Some are still delivered in paper.\u00a0 I want to focus on the counts of journal articles being delivered to Mathematical Reviews by the publishers.\u00a0 Our operations were interrupted by the pandemic.\u00a0 Therefore, including the counts of papers we retrieved would introduce confounding variables, which I prefer to avoid.\u00a0 I only have consistent data for these counts starting in 2017.\u00a0 Below is a graph of the counts by quarter from 2017 to 2020.\u00a0 It is evident from the graph that there were no extraordinary increases in 2020.<\/p>\n

\"Delivered<\/p>\n

The growth rates by year are<\/p>\n\n\n\n\n\n\n
Year<\/strong><\/td>\n% change from
\nprevious yr<\/strong><\/td>\n<\/tr>\n
2018<\/td>\n8.3%<\/td>\n<\/tr>\n
2019<\/td>\n0.3%<\/td>\n<\/tr>\n
2020<\/td>\n2.4%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

arXiv data: Mathematics<\/h3>\n

Finally, let’s look at some data from the arXiv.\u00a0 The arXiv is quite generous about making their data available<\/a>.\u00a0 In some cases, you can download a CSV file with data, or you can read it off tables.\u00a0 There were some types of data, though, where I had to do repeated searches to obtain what I was after.\u00a0 Even so, it is a fairly easy process.\u00a0 One benefit of these data are that we can count submissions<\/em>.<\/p>\n

Looking at all subjects in the arXiv over time, the growth in submissions<\/a> is clearly consistent and exponential.\u00a0 There are confounding factors, though.\u00a0 For instance, over the years, the subjects covered by the arXiv have expanded.\u00a0 Even so, looking at the data since 2010, it does not seem that 2020 was extraordinary.\u00a0 Indeed, last year’s growth rate was roughly the same as the growth rate in 2018.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Year<\/strong><\/td>\nCount<\/strong><\/td>\nRate<\/strong><\/td>\n<\/tr>\n
2010<\/td>\n70,131<\/td>\n9.5%<\/td>\n<\/tr>\n
2011<\/td>\n76,578<\/td>\n9.2%<\/td>\n<\/tr>\n
2012<\/td>\n84,603<\/td>\n10.5%<\/td>\n<\/tr>\n
2013<\/td>\n92,641<\/td>\n9.5%<\/td>\n<\/tr>\n
2014<\/td>\n97,517<\/td>\n5.3%<\/td>\n<\/tr>\n
2015<\/td>\n105,280<\/td>\n8.0%<\/td>\n<\/tr>\n
2016<\/td>\n113,380<\/td>\n7.7%<\/td>\n<\/tr>\n
2017<\/td>\n123,523<\/td>\n8.9%<\/td>\n<\/tr>\n
2018<\/td>\n140,616<\/td>\n13.8%<\/td>\n<\/tr>\n
2019<\/td>\n155,866<\/td>\n10.8%<\/td>\n<\/tr>\n
2020<\/td>\n178,329<\/td>\n14.4%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\"Graph<\/p>\n

Looking at counts of submissions in mathematics was more tedious.\u00a0 The arXiv provides visual information here<\/a>, but they do not provide a CSV file of the data.\u00a0 Therefore, I used the arXiv’s advanced search feature, searching a year at a time.\u00a0 It is possible to count papers in two ways: preprints that are only listed under mathematics and preprints that are in mathematics, but also cross-listed in another subject.\u00a0 The data for both searches, as well as the annual growth rates, are in the following table.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
arXiv math<\/strong><\/td>\n<\/tr>\n
Year<\/strong><\/td>\ncounts, with cross lists<\/strong><\/td>\ngrowth rate, with cross lists<\/strong><\/td>\ncounts, no cross lists<\/strong><\/td>\ngrowth rate, no cross lists<\/strong><\/td>\n<\/tr>\n
2009<\/td>\n14,928<\/td>\n<\/td>\n13,919<\/td>\n<\/td>\n<\/tr>\n
2010<\/td>\n17,626<\/td>\n18.1%<\/td>\n15,958<\/td>\n14.6%<\/td>\n<\/tr>\n
2011<\/td>\n20,202<\/td>\n14.6%<\/td>\n18,174<\/td>\n13.9%<\/td>\n<\/tr>\n
2012<\/td>\n22,946<\/td>\n13.6%<\/td>\n20,483<\/td>\n12.7%<\/td>\n<\/tr>\n
2013<\/td>\n25,742<\/td>\n12.2%<\/td>\n23,123<\/td>\n12.9%<\/td>\n<\/tr>\n
2014<\/td>\n27,693<\/td>\n7.6%<\/td>\n25,059<\/td>\n8.4%<\/td>\n<\/tr>\n
2015<\/td>\n30,002<\/td>\n8.3%<\/td>\n27,057<\/td>\n8.0%<\/td>\n<\/tr>\n
2016<\/td>\n31,488<\/td>\n5.0%<\/td>\n28,512<\/td>\n5.4%<\/td>\n<\/tr>\n
2017<\/td>\n33,407<\/td>\n6.1%<\/td>\n30,196<\/td>\n5.9%<\/td>\n<\/tr>\n
2018<\/td>\n35,416<\/td>\n6.0%<\/td>\n32,019<\/td>\n6.0%<\/td>\n<\/tr>\n
2019<\/td>\n38,055<\/td>\n7.5%<\/td>\n33,581<\/td>\n4.9%<\/td>\n<\/tr>\n
2020<\/td>\n41,027<\/td>\n7.8%<\/td>\n35,371<\/td>\n5.3%<\/td>\n<\/tr>\n
CAGR<\/strong><\/td>\n<\/td>\n6.5%<\/strong><\/td>\n<\/td>\n6.2%<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Looking at the data, the counts and the growth rates for 2020 do not stand out.\u00a0 Indeed, the CAGR for 2020 with cross listings is 6.5%, a bit below the observed rate for 2020.\u00a0 The CAGR for 2020 without cross listings is 6.2%, which is actually higher than the observed rate for 2020.<\/p>\n

Here is a graphical representation of the same data:<\/p>\n

\"Graphs<\/p>\n

arXiv data: Physics<\/h3>\n

For comparison, I looked at similar data for physics in the arXiv.\u00a0 \u00a0The growth rates for physics submissions to the arXiv, both with and without cross listings, were higher than recent years, and greater than the CAGRs for the two categories.\u00a0 The growth rate for physics in the arXiv has a lot of variation, though, making it hard to conclude if 2020 was an exceptional year or just a very good year.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
arXiv physics<\/strong><\/td>\n<\/tr>\n
Year<\/strong><\/td>\ncounts, with cross lists<\/strong><\/td>\ngrowth rate, with cross lists<\/strong><\/td>\ncounts, no cross lists<\/strong><\/td>\ngrowth rate, no cross lists<\/strong><\/td>\n<\/tr>\n
2009<\/td>\n45,567<\/td>\n<\/td>\n44,253<\/td>\n<\/td>\n<\/tr>\n
2010<\/td>\n47,831<\/td>\n5.0%<\/td>\n45,989<\/td>\n3.9%<\/td>\n<\/tr>\n
2011<\/td>\n51,115<\/td>\n6.9%<\/td>\n48,959<\/td>\n6.5%<\/td>\n<\/tr>\n
2012<\/td>\n53,378<\/td>\n4.4%<\/td>\n50,825<\/td>\n3.8%<\/td>\n<\/tr>\n
2013<\/td>\n55,844<\/td>\n4.6%<\/td>\n53,349<\/td>\n5.0%<\/td>\n<\/tr>\n
2014<\/td>\n56,944<\/td>\n2.0%<\/td>\n54,412<\/td>\n2.0%<\/td>\n<\/tr>\n
2015<\/td>\n59,742<\/td>\n4.9%<\/td>\n57,076<\/td>\n4.9%<\/td>\n<\/tr>\n
2016<\/td>\n61,598<\/td>\n3.1%<\/td>\n58,659<\/td>\n2.8%<\/td>\n<\/tr>\n
2017<\/td>\n62,557<\/td>\n1.6%<\/td>\n59,615<\/td>\n1.6%<\/td>\n<\/tr>\n
2018<\/td>\n65,937<\/td>\n5.4%<\/td>\n62,807<\/td>\n5.4%<\/td>\n<\/tr>\n
2019<\/td>\n69,009<\/td>\n4.7%<\/td>\n65,230<\/td>\n3.9%<\/td>\n<\/tr>\n
2020<\/td>\n74,181<\/td>\n7.5%<\/td>\n69,434<\/td>\n6.4%<\/td>\n<\/tr>\n
CAGR<\/strong><\/td>\n<\/td>\n3.5%<\/strong><\/td>\n<\/td>\n3.4%<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

<\/h3>\n

\"Graphs<\/p>\n

I also looked at monthly submission rates for mathematics and for physics for 2018 to 2020.\u00a0 There are definitely peaks and valleys in the monthly data, with both mathematics and physics having peaks around June – July 2020.<\/p>\n

\"Chart<\/p>\n

bioRxiv data<\/h3>\n

I also looked at data from the bioRxiv.\u00a0 Obtaining a list of monthly counts of submissions was fairly easy, using their API<\/a>.\u00a0 It is hard to interpret the data for this context, though.\u00a0 For one thing, the bioRxiv has only been operating since November 2013.\u00a0 Acceptance of the bioRxiv for preprints in biology and medicine is not yet as strong as the acceptance of the arXiv by mathematicians and physicists.\u00a0 \u00a0Mostly what the table shows is the growth of acceptance of the bioRxiv.\u00a0 \u00a0For completeness, here are the counts and the growth rates from the bioRxiv.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
Year<\/strong><\/td>\nNew papers<\/strong><\/td>\nGrowth rate<\/strong><\/td>\n<\/tr>\n
<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
2013<\/td>\n109<\/td>\n<\/td>\n<\/tr>\n
2014<\/td>\n886<\/td>\n713%<\/td>\n<\/tr>\n
2015<\/td>\n1,774<\/td>\n100%<\/td>\n<\/tr>\n
2016<\/td>\n4,721<\/td>\n166%<\/td>\n<\/tr>\n
2017<\/td>\n11,347<\/td>\n140%<\/td>\n<\/tr>\n
2018<\/td>\n20,783<\/td>\n83%<\/td>\n<\/tr>\n
2019<\/td>\n29,181<\/td>\n40%<\/td>\n<\/tr>\n
2020<\/td>\n38,717<\/td>\n33%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Conclusions<\/h2>\n

There does not seem to have been an extraordinary surge in mathematics papers in 2020 compared with previous years.\u00a0 As mentioned already, it is possible that some disciplines had increases because researchers without access to their labs had more time available to write.\u00a0\u00a0A survey of SpringerNature authors<\/a> indicated that, as a result of lockdowns, 65% of them intended to re-use their own data.\u00a0 About half of the respondents thought it is extremely<\/em> or somewhat<\/em> likely that the lockdown will result in the re-use of open data from other labs.\u00a0 The majority of mathematicians do not need to generate data in a laboratory to work.\u00a0 This may help to explain why mathematicians are not finding so much extra time to be writing papers during the pandemic.<\/p>\n

\n

Mathematical aside<\/h4>\n

Much of this post discusses changes to growth rates, i.e., second derivatives.<\/p>\n

<\/div>","protected":false},"excerpt":{"rendered":"

While many businesses have seen significant downturns during the pandemic, several scholarly publishers have reported increases in submissions in the first part of 2020. There are various studies and articles about the phenomenon.\u00a0 Meanwhile, at Mathematical Reviews, we have not … Continue reading →<\/span><\/a><\/p>\n

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