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

it is the only categorization, it may indicate users who engage with research through pure curi- osity, thus incarnate what we commonly refer to as the “general public” [46, 78]. Assignations to organizations represent both organizational accounts (universities, depart- ments, centers, governmental institutions, private companies, etc.) and individuals who employ expressions relating to these institutions [53]. Thus, the proportion of assignations to Organizations represent both these organizations through their specific accounts as well as individuals who use these organizations as identity markers. However, the Organizations cate- gory relies on words that have meanings beyond clear groups or institutions, such as “society”. A word like society may express a delineated entity, such as the “Society for X Research”, or an abstract entity, such as society as the realm of social interactions. Future research needs to take this into account, whether by adding to the dictionary, excluding problematic expressions, or refining interpretations, depending on the goals at hand. The relative frequencies of assignations within articles provide an overall assessment of the potential groups who shared research documents on Twitter. Focusing on a selection of highly tweeted papers in climate change research in 2015 and 2016, our results indicate that expres- sions relating to Academia and Personal identity markers are used to a large extent, whether through unique assignations or overlap other categories. The academic community is usually

the largest group sharing research on Twitter, with a diversity of different publics across indi- vidual papers. Meanwhile, political assignations look to be more present in papers discussing sensitive topics, such as fossil fuel consumption or the contribution of climate change to geo- political conflicts. Knowing how various publics engage with individual papers may help detect trends in public communication of research, both in general datasets or specific subsets. It may also help to document how papers circulate within specific communities. For example, we see quite different patterns between the papers Ecological networks are more sensitive to plant than to animal extinction under climate change and Oxygen isotope in archaeological bioapatites from India: Implications to climate change and decline of Bronze Age Harappan civilization. The first one has a significant share of users assigned to Academia, hereby indicating a signifi- cant participation by the research community. The other paper has the lowest share of aca- demic participation of the papers showcased in this study. These examples illustrate how estimates of the variety of users sharing individual papers provide a basis to further contextual- ize the repercussions of research dissemination on Twitter, especially for topics like climate change that resonate differently across distinct groups such as conservation specialists or con- cerned citizens. A qualitative survey of the results then provides meaning to these estimates and helps validate and refine each category.

Our study has some limits due to the mediated characteristics of Twitter data, and the epis- temological and technical choices made prior and through the design of the study. Word detection works as a proxy for the categorization of users but does not provide a direct assess- ment of “who” really participates to discussions about climate change research on Twitter [1, 28]. It is hardly possible to access the user behind an account through automated data analysis. We also rely on information chosen explicitly by the user and do not have access to all the choices made for the preparation of their Twitter profile description. While, this allows users to identify themselves to others in their own words and make their identities visible in ways they chose, our interpretations are based solely the identify markers we have access to. We also chose to categorize users Twitter profile by assigning categories to them and by going back and forth between an automatic method of expressions detection and a manual coding. These categories were chosen according the litterature to make sense of public research communication activities on Twitter [1, 3, 16, 28, 51]. We hypothesized that examin- ing the words and expressions employed by users would allow to investigate the extent to which various communities share climate change research on Twitter. Our analysis relies PLOS ONE Who tweets climate change research papers? PLOS ONE | https://doi.org/10.1371/journal.pone.0268999 June 3, 2022 12 / 17