PONE-D-21-17099Who tweets climate change papers? Investigating publics of research through users’ descriptionsPLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: N/A

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3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is a very interesting manuscript that touches upon an important topic (climate change) and employs a viable method (iterative textual analysis) to analyse Twitter data. Yet, while I see the potential of this approach and would highly like to encourage to continue and further refine this, there are some issues I have encountered that should be addressed in order to further enhance the quality of the manuscript

Introduction

- Please elaborate on what you mean by “messy data from Twitter” (lines 53-55)

- “As such, science communication and policy increasingly aim to understand the resonance of research in the public sphere.” (lines 58-59) – Really? Please provide more information on this and elaborate why you think this is the case. More specifically, policy has often been criticized for detaching itself from research and rather follow “popular opinion”.

Public conversations of climate change research on Twitter

- The cited articles (lines 71-82) seem to fit the argument. However, more information is needed on the specific studies, in order to better understand and contextualize their importance for this manuscript.

- “While patterns of scholarly communication on Twitter remain to be documented in detail, it is considered to have democratized access to research.” (lines 91-92) – this is a very bold statement and should be supported by further references. More specifically, one could argue that OER and OpenAccess publications have contributed more to this suggested process than Twitter.

- The authors refer to Haustein, as well as Diaz-Faes – this needs more information and elaboration as it appears to be key to the manuscript.

- What exactly are “non-elite” actors? (line 121)

Investigating and representing users in public communication of research on Twitter

- I am missing any link or reference to topics such as “fake news”, “post facts”, etc.

- “Our study focuses on the analysis of perceived users as a proxy of the publics of research communication on Twitter.” (line162-163) – ok, but is this common standard? Please provide a context that underlines that this is an agreed upon, or suggested approach.

- “As such, we account for the multiple identity markers mobilized in individual description to further assess the complexity through which a user may engage with research documents.” (lines 185-187) – ok, but do you also consider the chronological order to markers? For example, a user could be mother, activist and researcher. This is complex. But do you account for mother first and then researcher? One could argue that the list is a meaningful choice by the person.

Purpose of the study

- “As such, it is useful to assess another user position on Twitter, especially when there is no known relationship.” (lines 191-192) – true. But how can this be done without social network analysis? Please elaborate.

- “As such, our study analyzes perceived users through the mobilization of specific keywords in Twitter descriptions.” (lines 194-195) – this is very vague to me. At this stage of the manuscript, I am still not sure what “perceived users” and “mobilization of specific keywords” really means. Please elaborate and explain exactly what this is.

Data collection and Twitter metrics

- “They also were the latest years for which we had complete Twitter information at the time of data collection in September 2018.” (lines 234-236) – what does this really mean? Complete Twitter information can be quite a lot of things. Moreover, the authors indicated before that Twitter data is “messy”. So what does this really entail?

- “It also frequently appears in tweets sharing a link to a paper, and so is highly visible to all users.” (lines 237-238) – highly visible is, I believe, an overstatement. If an individual researcher shares the link to her paper and uses a commonly used hashtag, her post will more than likely drown in the information overload. Please elaborate.

- “we computed several Twitter metrics to further describe our dataset for tweet activity.” (lines 259-260) – which metrics did you compute? It becomes apparent later on, but I think it should be stated here.

- Overall, the paper does not explain, to the best of my knowledge, how users’ profile data was collected. Please make sure that this is included and properly described.

Textual analysis of Twitter profile descriptions

- The first paragraph (lines 297-308) remains descriptive and does not include any references to previous research that has done similar work. Please rectify this.

- “we then improved it through several iterations of the analysis.” (lines 314-315) – how exactly did you do this?

Presenting our observations

- Again this section remains rather descriptive and does not really strike a link to previous research and studies. Please provide more information on how the research fits into the larger picture.

Discussion

- “To circumvent some of these issues, our analysis focused on a method to assess perceived users as publics involved in climate change research Twitter communication.” (lines 486-487) – After reading the manuscript and argumentation, I am unfortunately not convinced that the authors can really make such a statement. The Tweets were selected based on DOI. This neglects a wide range of hashtags that are commonly used in this space, where the public gets their information and where researchers “need to tap-in to”, in order to gain recognition. I also wonder about the content of the Tweets – which has been neglected. How did people engage?

Conclusion

- “While our results do not provide a direct assessment of who tweet research due to the characteristics of Twitter data, it provides insights about how documents may permeate outside of academia and in specific groups.” (lines 600-602) – while I agree with the second part of the statement, I tend to disagree with the first part. Social Network Analyses, among others, has been proven as a valuable tool to analyze Twitter communication streams. Hence, the “messy nature” of Twitter data cannot explain why this manuscript has not provided applicable information. Overall, this is my main issue with the manuscript. The authors remain descriptive on a wide range of key issues that would justify the chosen method framework. Moreover, some more insights are not elaborated on and merely mentioned. Finally, some statements are made based on very shaky ground, particularly in view of previous, interdisciplinary research that has been done on Twitter communication. I would like to encourage the authors to carefully reconsider their argumentation and justification, in order to enhance the quality of the manuscript, which otherwise provides an interesting approach to the field.

Reviewer #2: Overall, I think the paper is clever and uses some interesting methodology and data. However, I think that language might be the major issue here, since using words such as 'engagement' and 'mobilised' would imply a very different type of analysis. For example, answering Q1 would require an analysis of actual engagement: likes, retweets, comments, quotes etc.

The authors state a more realistic and appropriate goal for the paper on pg. 14: " Rather, we understand expressions in Twitter descriptions as a proxy to investigate the potential publics engaging with specific scholarly documents." But even here, the word "engaging" is problematic. Simply sharing/retweeting a research article is not necessarily indicative of engagement. Other problematic terms that are used in the manuscript are ‘resonance’, and 'publics of climate change’; these are undefined terms and their relevance is not argued for. ‘Distinct communicational contexts’ is another example of wording that seems vague or conflated. What is the meaning of ‘context’ in this manuscript?

The main comment that thus arises is: What is actually the (main) research objective? Who (re)tweets papers? (user focused) or how documents may permeate a social media environment? Both current research questions are formulated too ambitious if I take a critical look at the type of analyses and results. It is hard to understand how user characteristics translate into indications of ‘resonance’ (RQ1). RQ2 focuses on ‘implications’, but based on what results? This questions seems more suitable for the Discussion.

At best, the paper could make claims about assessing the types of users/publics that contribute to the spreading of climate change research or co-creating a -- research informed -- climate change narrative. In many ways, the manuscript seems to be more a methodological paper (i.e. presenting an innovative methodology) than actually presenting meaningful results.

Other points that need attention:

Besides the need for a stronger rationale for the study, the introduction seems to provide opportunities for a stronger structure. Descriptive part and concluding remarks mixed haphazardly. Some sections show overlap or repetition (e.g., scholars including hyperlinks).

Structure in Methods is not very clear. Notably, information about article dataset is scattered throughout this section, and description is mixed with Twitter dataset.

The structure in the Results can be structured more clearly, as the focus shifts from papers to users and vice versa.

The Results seem more top-down than suggested in Introduction; because there are 8 predefined categories. Was there room for a more explorative examination of users? Otherwise I suggest building a stronger argument for these categories, and earlier in the manuscript.

Conclusions can be based more explicitly on results. I find it difficult to see the merit of percentages of user categories related to article titles. It seems a big ‘leap’ to conclusions based on the kind of data.

Reviewer #3: The manuscripts presents methodology developed to automatically detect certain keywords in Twitter profiles in order to learn and categorize the Twitter users to predefined categories. The results are promising and the authors write that their methods and system could be adapted to investigate Twitter users in general or some other specific subgroup, besides those connected to climate change research. It is' however, clear whether the scripts have been made or will be made openly available for other researchers to test and use.

The results are sound and discussed in detail. The authors also identify some caveats in their work and discuss those accordingly. The term "perceived users" needs a bit more explaining. The paper has some minor issues with the use of prepositions and between singular/plural form of words. Please check the following lines for such (and some minor typos): 55, 134, 152, 176, 184, 186, 190, 191, 201, 227, 237, 264, 278, 280, 285 (reference form), 287, 305, 359 (reference form), 380, 408, 416, 460, 502.

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Reviewer #1: No

Reviewer #2: Yes: Bob C Mulder

Reviewer #3: No

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Who tweets climate change papers? Investigating publics of research through users’ descriptions

PONE-D-21-17099R1

Dear Dr. Toupin,

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