Abstract

The goal of the open access (OA) movement is to help everyone access the scholarly research, not just those who can afford to. However, most studies looking at whether OA has met this goal have focused on whether other scholars are making use of OA research. Few have considered how the broader public, including the news media, uses OA research. This study sought to answer whether the news media mentions OA articles more or less than paywalled articles by looking at articles published from 2010 through 2018 in journals across all four quartiles of the Journal Impact Factor using data obtained through Altmetric.com and the Web of Science. Gold, green and hybrid OA articles all had a positive correlation with the number of news mentions received. News mentions for OA articles did see a dip in 2018, although they remained higher than those for paywalled articles.


Authors

Teresa Schultz

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  • 1 reviewer
  • pre-publication peer review (FINAL ROUND)
    Decision Letter
    2021/05/16

    16-May-2021

    Dear Ms. Auch Schultz:

    It is a pleasure to accept your manuscript entitled "All the Research That's Fit to Print: Open Access and the News Media" for publication in Quantitative Science Studies.

    I would like to request you to prepare the final version of your manuscript using the checklist available at https://tinyurl.com/qsschecklist. Please also sign the publication agreement, which can be downloaded from https://tinyurl.com/qssagreement. The final version of your manuscript, along with the completed checklist and the signed publication agreement, can be returned to qss@issi-society.org.

    Thank you for your contribution. On behalf of the Editors of Quantitative Science Studies, I look forward to your continued contributions to the journal.

    Best wishes,
    Dr. Ludo Waltman
    Editor, Quantitative Science Studies
    qss@issi-society.org

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    Author Response
    2021/05/08

    Response 2 to QSS editor
    1. Reviewer 1 expressed concerns about PLOS One articles over affecting the results for gold OA articles. In response, I created a new subset of my data that took out all PLOS One articles and reran some of my analysis. The percent of gold OA articles that received any news mention actually increased slightly, from 11% to 13.5%. When looking at just gold OA articles that did receive a news mention, the median number of news mentions remained the same at 3. And finally, I reran the zero-inflated negative binomial analysis, and the results were similar.

    For the count portion:
    i. Coefficient for gold OA with and without PLOS One was 0.52
    ii. Z with PLOS one was 25.95; without was 24.85
    iii. Exp(coefficient) with and without PLOS One was 1.7
    iv. 95% confidence intervals with PLOS One were 0.49 and 0.57; without were 0.48 and 0.56.

    For the excess zeroes portion:
    i. Coefficient for gold OA with PLOS One was -0.93; without was -0.84
    ii. Z with PLOS One was -40.58; without was -33.46
    iii. Exp(coefficient) with PLOS One was 0.39; without was 0.43
    iv. 95% confidence intervals with PLOS one were -0.98 and -0.89; without were -0.89 and -0.79.

    Because of the above results, I do not think continuing to include PLOS One articles in the study sample skews the results.

    1. In response to the reviewers concerns about issues between hybrid and green OA and journalists, I’ve added text starting at line 281 in the Limitations section to address these. As far as the concern about when green OA articles were actually made open, I already addressed that in the limitations section starting at line 278.

    2. It appears there’s some confusion about the excess zeroes portion of the zero inflated negative binomial model. It actually is measuring the likelihood of news articles to NOT have any news mentions. So a negative coefficient would mean a variable is less likely to have excess zeroes, or more likely to have received at least one news mention. I’ve relied on UCLA’s Statistical Consulting page on ZINB for this interpretation. I’ve attempted to add language in the article at line 318-319 to clarify this.

    3. In regards to the confusion between the statement “The majority for first quartile articles increased to 91% of articles receiving a news mention” and Table 9, that table actually reflects the information in the next sentence, so I moved the in-text reference to the table so it follows that sentence, which ends on Line 376. As far as the incongruence between the results for JIF in the ZINB analysis and the descriptive statistics, I do agree they appear strange and was quite surprised by it. However, I would also argue that Table 9 points to some explanation (if not entirely). Paywalled articles do make up a slightly higher proportion of articles in Q1 receiving a news mention compared to their proportion of all articles in Q1 (15% vs. 21%), but the opposite is true for all other quartiles, and often by a lot. For instance, all OA articles make up just 43% of all articles in Q2 but then make up 70% of articles in Q2 that received a news mention. So clearly, while JIF does play a role, OA status does as well. Although much of this is due to green/hybrid OA articles, some of it is also gold OA articles, where their share either increased in comparison to paywalled articles or did not decrease as much as paywalled articles. I have added to the discussion section (see lines 439-445) to address this.

    Thank you to the editor and reviewers for their continued work on this article.

    Teresa Schultz

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  • pre-publication peer review (ROUND 2)
    Decision Letter
    2021/04/11

    11-Apr-2021

    Dear Ms. Auch Schultz:

    Your manuscript QSS-2020-0073.R1 entitled "All the Research That's Fit to Print: Open Access and the News Media", which you submitted to Quantitative Science Studies, has been reviewed. Your revised manuscript was sent to reviewers 1 and 2 that also reviewed the original version of your work. The comments of the reviewers are included at the bottom of this letter.

    Reviewer 2 recommends acceptance of your manuscript, while reviewer 1 recommends a second revision. Based on the comments of the reviewers, my editorial decision is to invite you to prepare a second revised version of your manuscript. In this revision, please try to address the remaining comments of reviewer 1.

    To revise your manuscript, log into https://mc.manuscriptcentral.com/qss and enter your Author Center, where you will find your manuscript title listed under "Manuscripts with Decisions." Under "Actions," click on "Create a Revision." Your manuscript number has been appended to denote a revision.

    You may also click the below link to start the revision process (or continue the process if you have already started your revision) for your manuscript. If you use the below link you will not be required to login to ScholarOne Manuscripts.

    PLEASE NOTE: This is a two-step process. After clicking on the link, you will be directed to a webpage to confirm.

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    You will be unable to make your revisions on the originally submitted version of the manuscript. Instead, revise your manuscript using a word processing program and save it on your computer. Please also highlight the changes to your manuscript within the document by using the track changes mode in MS Word or by using bold or colored text.

    Once the revised manuscript is prepared, you can upload it and submit it through your Author Center.

    When submitting your revised manuscript, you will be able to respond to the comments made by the reviewers in the space provided. You can use this space to document any changes you make to the original manuscript. In order to expedite the processing of the revised manuscript, please be as specific as possible in your response to the reviewers.

    IMPORTANT: Your original files are available to you when you upload your revised manuscript. Please delete any redundant files before completing the submission.

    If possible, please try to submit your revised manuscript by 09-Aug-2021. Let me know if you need more time to revise your work.

    Once again, thank you for submitting your manuscript to Quantitative Science Studies and I look forward to receiving your revision.

    Best wishes,
    Dr. Ludo Waltman
    Editor, Quantitative Science Studies
    qss@issi-society.org

    Reviewers' Comments to Author:

    Reviewer: 1

    Comments to the Author

    Dear Author,
    Thanks for the updated manuscript and list of revisions from the previous version of the manuscript. I also appreciate the inclusion of the journal data. Many of the points from my previous review have been addressed. Unfortunately, some of the main criticisms from my previous review remain, which I highlight below:

    Sample Selection

    I am still not convinced that the sample selection is fair, especially with respect to the inclusion of mega-journals which will have an undue influence on later results. In particular, PLOS ONE contributes nearly half of all articles in the gold OA group. This means that the effect of “Gold OA”, as reported in the regression results, is influenced nearly 50% by the news activity of articles in PLOS ONE, and so does not necessarily represent the effect of a certain type of access as much as it reflects the marketing and dissemination strategy of a single journal.

    As I mentioned in my previous review, the way in which the journals are sampled from quartiles also appears problematic. For example, in Social Sciences, there are 11 gold OA which all derive from Q3 and Q4 in terms of journal impact factors (8 of which are non-English language journals), and 20 paywalled journals spread over Q1 to Q4 (all English language journals). Whilst JIF is incorporated as a predictor in the regression results, it is not discussed in the later descriptive analysis of variation within disciplines (section 5.1): the results here suggest that gold OA journals receive very few news mentions in comparison to paywalled or green/hybrid journals, but it is not clear that the gold OA journals represent journals with much lower JIFs, and mainly non-English language journals that may not be covered as extensively in the sources tracked by Altmetric.com, which tend to lean towards English-language outlets.

    On a minor point, there seems to be some journals included that have not published any articles, at least according to the data that the authors have shared – I assume that this is because articles in those journals could not be matched between WoS and Altmetric.com, although this point could be clarified – at least one of the journals appeared to have valid DOIs when I checked.

    OA classification

    A point made in my last review is that the categorisation of green/hybrid in a single category seems problematic. The author has replied “However, I also dispute that we can assume journalists care (or are even aware about) the distinction between the two. Google Scholar crawls both and has been shown to be the best tool available for finding green OA versions, so one is not necessarily harder than the other to find”. I am still not entirely convinced by this, for two main reasons. The first is as I wrote in my previous review, that these might represent different routes for a journalist to search/access an article. One requires simply accessing a journal page (possibly through a link contained in a press release), and the other requires at least some degree of knowledge of academic search engines. If it is the case that journalists can locate articles easily (e.g. through Google Scholar, although this may differ in its coverage of green OA compared to Altmetric/Unpaywall), then some discussion of this in the manuscript would be helpful.

    The second reason is that green and hybrid OA reflect different routes from the authors perspective. Often (but not always) publishing an article in a hybrid journal requires a hefty APC – these articles are likely more reflective of authors from well-funded research projects/countries who can afford such fees, in comparison to Green OA which is usually free. Authors may also preferentially select their most novel/exciting work to publish hybrid OA which would also be the most likely work to receive news coverage.

    Another technical point here is that news mentions tend to accrue relatively quickly following publication of an article, but Altmetric.com presumably do not give an indication of when an article became green OA – it is possibly that a proportion of those articles were made green OA following 12-24 month embargo periods, after which an article is unlikely to be attractive for news reporting.

    Regression analysis

    There still appears to be a disconnect between the regression results and the later discussion (section 6). For example, the discussion generally implies that OA had a positive effect on news mentions. But in the excess-zeroes part of the regression model, gold OA and green/hybrid OA have exponentiated coefficients of 0.39 and 0.18, respectively. If I am understanding correctly (and I am not a statistician, so feel free to correct me), this means that gold OA is 2.6 times (i.e. 1/0.39) less likely to be mentioned in a news article compared to a paywalled article, and hybrid/green OA are 5.55 times less likely to be mentioned. Conversely, in the counts portion of the regression model, gold OA and green/hybrid OA receive 1.7 and 3.3 times more news mentions in total than paywalled articles. The interpretation is therefore that fewer OA articles are mentioned in news articles, but those that are mentioned are reported on much more intensively. In looking at this issue I compared these results to those of Dehdaridad and Didegah (2020; http://doi.org/10.29024/joa.29), who did the same type of regression analysis for news article mentions of OA vs non-OA articles in Life Sciences and Biomedicine. They reported a similar coefficient for the count portion of the model (1.84) but a much larger coefficient for the excess-zeroes part of the model (2.53). Although they only analyse one discipline and account for a different number of variables in their regression model, comparing the two results sets would be interesting.

    As mentioned in the previous review, it is also difficult to reconcile the small effect for JIF in the counts portion of the regression results (exponentiated coefficient of 1.02), with the seemingly large effect of JIF on news articles discussed in section 5.2, where 72% of articles in JIF Q1 JIF receive 91% of all news article mentions (note: I struggled to connect the text of section 5.2 with Table 9, e.g. this sentence: “The majority for first quartile articles increased to 91% of articles receiving a news mention (Table 9)” does not seem to fit with table 9, or at least I cannot see where the 91% figure is arrived at from the table).

    Minor points

    Line 240: I would rather say a DOI is a unique identifier than a unique number (as DOI also contains characters)

    Reviewer: 2

    Comments to the Author

    The author has approached most of my comments. The manuscript can be accepted for publication.

    Decision letter by
    Cite this decision letter
    Reviewer report
    2021/04/11

    The author has approached most of my comments. The manuscript can be accepted for publication.

    Reviewed by
    Cite this review
    Reviewer report
    2021/04/09

    Dear Author,
    Thanks for the updated manuscript and list of revisions from the previous version of the manuscript. I also appreciate the inclusion of the journal data. Many of the points from my previous review have been addressed. Unfortunately, some of the main criticisms from my previous review remain, which I highlight below:

    Sample Selection

    I am still not convinced that the sample selection is fair, especially with respect to the inclusion of mega-journals which will have an undue influence on later results. In particular, PLOS ONE contributes nearly half of all articles in the gold OA group. This means that the effect of “Gold OA”, as reported in the regression results, is influenced nearly 50% by the news activity of articles in PLOS ONE, and so does not necessarily represent the effect of a certain type of access as much as it reflects the marketing and dissemination strategy of a single journal.

    As I mentioned in my previous review, the way in which the journals are sampled from quartiles also appears problematic. For example, in Social Sciences, there are 11 gold OA which all derive from Q3 and Q4 in terms of journal impact factors (8 of which are non-English language journals), and 20 paywalled journals spread over Q1 to Q4 (all English language journals). Whilst JIF is incorporated as a predictor in the regression results, it is not discussed in the later descriptive analysis of variation within disciplines (section 5.1): the results here suggest that gold OA journals receive very few news mentions in comparison to paywalled or green/hybrid journals, but it is not clear that the gold OA journals represent journals with much lower JIFs, and mainly non-English language journals that may not be covered as extensively in the sources tracked by Altmetric.com, which tend to lean towards English-language outlets.

    On a minor point, there seems to be some journals included that have not published any articles, at least according to the data that the authors have shared – I assume that this is because articles in those journals could not be matched between WoS and Altmetric.com, although this point could be clarified – at least one of the journals appeared to have valid DOIs when I checked.

    OA classification

    A point made in my last review is that the categorisation of green/hybrid in a single category seems problematic. The author has replied “However, I also dispute that we can assume journalists care (or are even aware about) the distinction between the two. Google Scholar crawls both and has been shown to be the best tool available for finding green OA versions, so one is not necessarily harder than the other to find”. I am still not entirely convinced by this, for two main reasons. The first is as I wrote in my previous review, that these might represent different routes for a journalist to search/access an article. One requires simply accessing a journal page (possibly through a link contained in a press release), and the other requires at least some degree of knowledge of academic search engines. If it is the case that journalists can locate articles easily (e.g. through Google Scholar, although this may differ in its coverage of green OA compared to Altmetric/Unpaywall), then some discussion of this in the manuscript would be helpful.

    The second reason is that green and hybrid OA reflect different routes from the authors perspective. Often (but not always) publishing an article in a hybrid journal requires a hefty APC – these articles are likely more reflective of authors from well-funded research projects/countries who can afford such fees, in comparison to Green OA which is usually free. Authors may also preferentially select their most novel/exciting work to publish hybrid OA which would also be the most likely work to receive news coverage.

    Another technical point here is that news mentions tend to accrue relatively quickly following publication of an article, but Altmetric.com presumably do not give an indication of when an article became green OA – it is possibly that a proportion of those articles were made green OA following 12-24 month embargo periods, after which an article is unlikely to be attractive for news reporting.

    Regression analysis

    There still appears to be a disconnect between the regression results and the later discussion (section 6). For example, the discussion generally implies that OA had a positive effect on news mentions. But in the excess-zeroes part of the regression model, gold OA and green/hybrid OA have exponentiated coefficients of 0.39 and 0.18, respectively. If I am understanding correctly (and I am not a statistician, so feel free to correct me), this means that gold OA is 2.6 times (i.e. 1/0.39) less likely to be mentioned in a news article compared to a paywalled article, and hybrid/green OA are 5.55 times less likely to be mentioned. Conversely, in the counts portion of the regression model, gold OA and green/hybrid OA receive 1.7 and 3.3 times more news mentions in total than paywalled articles. The interpretation is therefore that fewer OA articles are mentioned in news articles, but those that are mentioned are reported on much more intensively. In looking at this issue I compared these results to those of Dehdaridad and Didegah (2020; http://doi.org/10.29024/joa.29), who did the same type of regression analysis for news article mentions of OA vs non-OA articles in Life Sciences and Biomedicine. They reported a similar coefficient for the count portion of the model (1.84) but a much larger coefficient for the excess-zeroes part of the model (2.53). Although they only analyse one discipline and account for a different number of variables in their regression model, comparing the two results sets would be interesting.

    As mentioned in the previous review, it is also difficult to reconcile the small effect for JIF in the counts portion of the regression results (exponentiated coefficient of 1.02), with the seemingly large effect of JIF on news articles discussed in section 5.2, where 72% of articles in JIF Q1 JIF receive 91% of all news article mentions (note: I struggled to connect the text of section 5.2 with Table 9, e.g. this sentence: “The majority for first quartile articles increased to 91% of articles receiving a news mention (Table 9)” does not seem to fit with table 9, or at least I cannot see where the 91% figure is arrived at from the table).

    Minor points

    Line 240: I would rather say a DOI is a unique identifier than a unique number (as DOI also contains characters)

    Reviewed by
    Cite this review
    Author Response
    2021/03/23

    To the QSS Editor,

    I have finished making revisions to my article, All the News That’s Fit to Print: Open Access and the News Media, in response to peer reviewer comments. See below for a list of changes I made (tracked in the document as well):

    • The issue with implying causation – I have gone through my article and tried to take out language suggesting effect. For instance, I have changed the language in the research questions to denote a relationship instead.
    • Confusion with the methodology section – I have tried to pare down the methodology section and introduce tables to simplify the process and make it easier to understand. Reviewers had suggested a visual perhaps, but it did not seem to help when I attempted this. I hope the changes I did make address these concerns.
    • Confusion over how OA status was determined and what was labeled as which OA type – I already noted in the methodology that the study relied on Altmetric.com to identify green/hybrid OA articles (see line 219-220). I added language starting on line 221 to note that any article from a gold OA journal was marked as gold OA.
    • Inconsistency with numbers in the text and as reported in the first table in the Results – I thank the reviewer for spotting this. The number in the text was written before I deleted the PNAS articles from my study sample, and I forgot to update it. I’ve changed it so it now matches with the table.
    • Issues with the X-axis of the figures – I did not see any issue with this, but I’m assuming problems came up because I had copied and pasted the figures from Microsoft Excel. I have instead replaced them with PNG file images of the graphs, which will hopefully fix any issues with the X axis.
    • How were the years of News mention determined? – I’ve added text at line 226 in the methodology to note this metadata was gathered by Altmetric.com. I’ve also added text at line 288 in the Limitations to note that it’s unclear when Altmetric.com added their various news sources, which in turn could have affected the rate of news mentions over time.
    • Advantage of Arxiv papers over Repec papers because Altmetric.com tracks Arxiv papers – I do not see how this would play a role in this study. Altmetric.com tracks the news mentions of the scholarly articles from the news articles themselves; therefore, it does not necessarily matter if Altmetric.com is tracking the source.
    • Language – I have gone through and made some small changes to address any grammar issues.
    • Incorporate results from three suggested articles/reports – I reviewed these and have added language to my Lit Review citing them. Thank you to the reviewers for these suggestions.
    • Lack of results/request for better incorporation of descriptive statistics – I have provided some more descriptive data, especially in the parts of the results discussing the subjects and journal quartiles of the articles, in response to this. Further analysis is outside the scope of this current project, although is a ripe area for a future study.
    • Confusion between tables 4 & 5 – I have added wording to the title for Table 4 (now called Table XXX) to clarify it is looking at all articles, vs. Table 5 (now called Table XXX), which looked specifically at OA articles.
    • Selection of journals and why I settled on top five journals from each quartile, and suggestion of discussion of potential biases – I wanted a sample large enough that would allow for various data analysis but not so large as to make data analysis impractical. I tested out this number of journals and deemed the resulting study sample appropriately large enough for my purposes. As for biases, I’ve added language (starting at line 298) to discuss the issues with having mega journals such as PLOS One and Scientific Reports make up such a large portion of the study sample.
    • Provide dataset with journal names, articles/year, JIF, and provide summary by subject in text of manuscript – I have created a dataset, which I will upload with my revised article, that provides a record for each journal, as well as the total number of articles included in the study sample from the journal, the 2018 JIF of the journal, the quartile of the journal, and whether the journal was gold OA. I have also added a table on page 13 providing the requested information. I’ve also clarified that the JIF is from 2018.
    • Concern over combining green/hybrid – I attempted to better separate these two categories as suggested using Unpaywall data. However, it appears they’ve changed how researchers can access this data, and at this time I am unable to. However, I also dispute that we can assume journalists care (or are even aware about) the distinction between the two. Google Scholar crawls both and has been shown to be the best tool available for finding green OA versions, so one is not necessarily harder than the other to find. I think this is a ripe area for future study and do plan on pursuing this research question in a later article.
    • Concern over the use of Eigenfactor as an independent variable – I had a list of potential variables I was interested in exploring and began combining them and testing them using the AIC. The Eigenfactor was the second variable I added, after the JIF, and as the AIC showed positive results, continued to include it in my other iterations. I understand the concern of the reviewer, however, and again tested this without the Eigenfactor, and the AIC suggested this was a better formula. Thus, I have taken out the Eigenfactor and rerun my zero-inflated binomial model and have updated the tables in the text with the new results. Although the numbers did change over all, there was no change as far as positive or negative correlations.
    • Add 95% confidence intervals to the tables – I have done this.
    • Addressing mechanism of how journalists report in Discussion section – I have added language to address this starting at line 419.
    • Question over news mentions having greater weight – I have added a citation at line 122 to address this.
    • Interpretation of Fraser et al. – I have clarified the language describing this study to better reflect it (see line 147).

    Thank you for your consideration.
    Teresa Auch Schultz

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  • pre-publication peer review (ROUND 1)
    Decision Letter
    2020/11/22

    22-Nov-2020

    Dear Ms. Auch Schultz:

    Your manuscript QSS-2020-0073 entitled "All the Research That's Fit to Print: Open Access and the News Media", which you submitted to Quantitative Science Studies, has been reviewed. There are three reviewers. The comments of reviewers 2 and 3 are included at the bottom of this letter. The comments of reviewer 1, who has chosen to reveal his identity, can be found in the attached PDF file.

    Based on the comments of the reviewers as well as my own reading of your manuscript, my editorial decision is to invite you to prepare a major revision of your manuscript.

    To revise your manuscript, log into https://mc.manuscriptcentral.com/qss and enter your Author Center, where you will find your manuscript title listed under "Manuscripts with Decisions." Under "Actions," click on "Create a Revision." Your manuscript number has been appended to denote a revision.

    You may also click the below link to start the revision process (or continue the process if you have already started your revision) for your manuscript. If you use the below link you will not be required to login to ScholarOne Manuscripts.

    PLEASE NOTE: This is a two-step process. After clicking on the link, you will be directed to a webpage to confirm.

    https://mc.manuscriptcentral.com/qss?URL_MASK=6c9a95a69733437c8b11dff03692e2cf

    You will be unable to make your revisions on the originally submitted version of the manuscript. Instead, revise your manuscript using a word processing program and save it on your computer. Please also highlight the changes to your manuscript within the document by using the track changes mode in MS Word or by using bold or colored text.

    Once the revised manuscript is prepared, you can upload it and submit it through your Author Center.

    When submitting your revised manuscript, you will be able to respond to the comments made by the reviewers in the space provided. You can use this space to document any changes you make to the original manuscript. In order to expedite the processing of the revised manuscript, please be as specific as possible in your response to the reviewers.

    IMPORTANT: Your original files are available to you when you upload your revised manuscript. Please delete any redundant files before completing the submission.

    If possible, please try to submit your revised manuscript by 22-Mar-2021. Let me know if you need more time to revise your work.

    Once again, thank you for submitting your manuscript to Quantitative Science Studies and I look forward to receiving your revision.

    Best wishes,
    Dr. Ludo Waltman
    Editor, Quantitative Science Studies
    qss@issi-society.org

    Reviewers' Comments to Author:

    Reviewer: 1

    Comments to the Author
    Please find my review attached. Do not hesitate to contact me with any questions or to clarify any of the points.

    Reviewer: 2

    Comments to the Author
    The manuscript submitted presents an interesting study of the relationship between the OA status of scientific publication and the mentioning and dissemination of these publications via new media (as captured by Altmetric.com).
    As such the study is interesting and the results are worth publishing. However, the current version of the manuscript presents some important deficiencies that need to be addressed before it can be accepted for publications.
    - The notions of “effects”. Although at the end of the manuscript is clearly stated that more research is needed in order to determine any “causation effect’, the impression given in the early sections of the manuscript suggest that this is the aim. For example, the Research Questions read about “influence” and “interaction”. Probably “relationship” would be a much better term here. In any case, I suggest to review the manuscript to remove all tentative mentions to any causality/effect, and clearly state the descriptive nature of the research.
    - Methodological issues. The Methodology section is particularly problematic. I recommend to present some graphical or summarized outline of the data collection process. The current version is a bit hard to read and it is easy to get lost on the different filtering steps and datasets created.
    - Another important methodological issue is that is not clearly explained how OA is determined. According to the current reading of the paper, the OA information seems to come from Altmetric.com, however this methodology is not properly described in the manuscript. Since this is an important aspect of the manuscript, the approach how publications are classified as Green, Gold or hybrid need to be clarified. In addition, it would also be important to explicitly explain what happens to those publication that fall in more than one category, particularly those that can both be Green and Gold, or Green and hybrid.
    - Results. The results section is also problematic. There are important inconsistencies in the presentation of the results. For example, the numbers presented in Table 1 do not seem to match the text about the table. Thus, in the text it is mentioned that “Overall 14% (87,841) of all articles received at least one news mention”; however in the table we read 77,255, which amounts to about 13% of All the publication articles.
    - Figure 1 has the labels of the x-axis wrong.
    - How were the “Year of News Mention” determined (section 5.4)? Is this information extracted from Altmetric.com? Could there be any data issues in there? The sudden peak in the news mentions between 2015 and 2016 raises the question whether this is a genuine increase in news, or caused by methodological changes in the news tracking approach of Altmetric.
    - In the conclusions sections there are also some remarks that would need some reconsideration. For example, it is argued that Arxiv may be the main reason to explain the large share of green OA in Astrophysics, while this is not the case for business and economics (having a repository like RePEc). However, Arxiv papers are tracked by Altmetric, which may provide them and advantage over RePEc. I recommend the author to check this extent.
    - Language. Although the paper can be properly understood, it would be important to perform a check to the English language. There are some language inconsistencies here and there (e.g. lack of concordance of subjects and verbs, etc.) that make the reading a bit confusing at times.
    - Other recommendations. I believe the general outcome of the manuscript is relevant and interesting. Perhaps the author could consider the results reported at the Open Science Monitor of the EC, since roughly they also support the outcomes of the manuscript, by showing how the majority of (social) media activity around scientific papers concentrates around OA papers.[https://ec.europa.eu/info/research-and-innovation/strategy/goals-research-and-innovation-policy/open-science/open-science-monitor/trends-open-access-publications_en#altmetrics]

    Reviewer: 3

    Comments to the Author
    The manuscript is well written and presents some interesting results about the use of OA articles by news media. My main concern is that with such rich material spanning several years the authors could have done more. As the authors also accurately reference in the manuscript, there are many similar studies (albeit not that many investigating OA in news media) using similar or even same methodology and data. To make a more significant contribution the authors could have dug deeper into the data, for instance by looking closer at differences over time. The results, as they are now, are a bit thin. In addition, the authors should more clearly return to the research questions in the end.
    Specific issues:
    RQ2 needs some rewording.
    I don't really understand the difference between tables 4 and 5? How come the "number of OA articles with at least one news mention" be the same for some journals and different for other journals between tables 4 and 5?

    Decision letter by
    Cite this decision letter
    Reviewer report
    2020/11/09

    The manuscript is well written and presents some interesting results about the use of OA articles by news media. My main concern is that with such rich material spanning several years the authors could have done more. As the authors also accurately reference in the manuscript, there are many similar studies (albeit not that many investigating OA in news media) using similar or even same methodology and data. To make a more significant contribution the authors could have dug deeper into the data, for instance by looking closer at differences over time. The results, as they are now, are a bit thin. In addition, the authors should more clearly return to the research questions in the end.
    Specific issues:
    RQ2 needs some rewording.
    I don't really understand the difference between tables 4 and 5? How come the "number of OA articles with at least one news mention" be the same for some journals and different for other journals between tables 4 and 5?

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    Reviewer report
    2020/10/25

    The manuscript submitted presents an interesting study of the relationship between the OA status of scientific publication and the mentioning and dissemination of these publications via new media (as captured by Altmetric.com).
    As such the study is interesting and the results are worth publishing. However, the current version of the manuscript presents some important deficiencies that need to be addressed before it can be accepted for publications.
    - The notions of “effects”. Although at the end of the manuscript is clearly stated that more research is needed in order to determine any “causation effect’, the impression given in the early sections of the manuscript suggest that this is the aim. For example, the Research Questions read about “influence” and “interaction”. Probably “relationship” would be a much better term here. In any case, I suggest to review the manuscript to remove all tentative mentions to any causality/effect, and clearly state the descriptive nature of the research.
    - Methodological issues. The Methodology section is particularly problematic. I recommend to present some graphical or summarized outline of the data collection process. The current version is a bit hard to read and it is easy to get lost on the different filtering steps and datasets created.
    - Another important methodological issue is that is not clearly explained how OA is determined. According to the current reading of the paper, the OA information seems to come from Altmetric.com, however this methodology is not properly described in the manuscript. Since this is an important aspect of the manuscript, the approach how publications are classified as Green, Gold or hybrid need to be clarified. In addition, it would also be important to explicitly explain what happens to those publication that fall in more than one category, particularly those that can both be Green and Gold, or Green and hybrid.
    - Results. The results section is also problematic. There are important inconsistencies in the presentation of the results. For example, the numbers presented in Table 1 do not seem to match the text about the table. Thus, in the text it is mentioned that “Overall 14% (87,841) of all articles received at least one news mention”; however in the table we read 77,255, which amounts to about 13% of All the publication articles.
    - Figure 1 has the labels of the x-axis wrong.
    - How were the “Year of News Mention” determined (section 5.4)? Is this information extracted from Altmetric.com? Could there be any data issues in there? The sudden peak in the news mentions between 2015 and 2016 raises the question whether this is a genuine increase in news, or caused by methodological changes in the news tracking approach of Altmetric.
    - In the conclusions sections there are also some remarks that would need some reconsideration. For example, it is argued that Arxiv may be the main reason to explain the large share of green OA in Astrophysics, while this is not the case for business and economics (having a repository like RePEc). However, Arxiv papers are tracked by Altmetric, which may provide them and advantage over RePEc. I recommend the author to check this extent.
    - Language. Although the paper can be properly understood, it would be important to perform a check to the English language. There are some language inconsistencies here and there (e.g. lack of concordance of subjects and verbs, etc.) that make the reading a bit confusing at times.
    - Other recommendations. I believe the general outcome of the manuscript is relevant and interesting. Perhaps the author could consider the results reported at the Open Science Monitor of the EC, since roughly they also support the outcomes of the manuscript, by showing how the majority of (social) media activity around scientific papers concentrates around OA papers.[https://ec.europa.eu/info/research-and-innovation/strategy/goals-research-and-innovation-policy/open-science/open-science-monitor/trends-open-access-publications_en#altmetrics]

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    Reviewer report
    2020/10/15

    Please find my review attached. Do not hesitate to contact me with any questions or to clarify any of the points.

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