altmetrics18:  Science & the public : public interactions with science through the lens of social medi

Haustein, Stefanie

Toupin, Rémi

English

Université de Montréal

Research-in-progress - altmetrics18 
 
A climate of sharing:  
Who are the users engaging with climate research on Twitter? 
 
Rémi Toupin1,2,5 & Stefanie Haustein3,4,5 
1 toupin.remi@uqam.ca 
Laboratoire de communication médiatisée par ordinateur (LabCMO), 
Université du Québec à Montréal, Montréal (Canada) 
2 Canada Research Chair on the Transformations of Scholarly Communication, Université de Montréal, Montréal 
(Canada) 
5ScholCommLab, University of Ottawa, Ottawa and Simon Fraser University, Vancouver (Canada) 
 
3 stefanie.haustein@uottawa.ca 
School for Information Studies, University of Ottawa, Ottawa (Canada) 
4 Centre interuniversitaire de recherche sur la science et la technologie (CIRST), 
Université du Québec à Montréal, Montréal (Canada) 
5ScholCommLab, University of Ottawa, Ottawa and Simon Fraser University, Vancouver (Canada) 
 
 
Introduction 
As Twitter is used by a wide variety of users — many of whom outside the scientific 
community — it is presumed to broaden the spectrum of public engagement with 
research. Apart from serving as a platform for science communication, Twitter has been 
considered in the context of developing new metrics which aim to measure the societal 
impact of research, so called altmetrics. However, the conceptualization and application 
of altmetrics prove to be a challenge so far, mainly due to a lack of understanding of the 
heterogeneous acts and different levels of engagement as well as the diverse user base 
on social media (Haustein, Bowman, & Costas, 2016a). 
The identification of users engaging with research on Twitter—particularly those that are 
considered non-academic—has been a key issue in defining scholarly Twitter metrics, as 
personal information is mostly limited to Twitter bios of 160 characters. Studies have 
applied codebooks to classify accounts maintained by institutions (e.g., universities, 
media, publishers, non-profits), individuals (e.g., researchers, students, professionals, 
science communicators) or automated profiles (i.e., bots) based on information provided 
in the Twitter bio (Haustein et al., 2016b; Holmberg et al., 2014; Tsou et al., 2015). 
However, it must be noted that the boundaries between categories are blurred as users 
may fall into more than one, making overlapping classification essential. The identification 
of non-academic (or lay) users has been particularly challenging, since their Twitter bios 
do not contain specific keywords identifying them as such, or they might not tweet links 
to scientific papers when communicating about science on Twitter (Bowman, 2015 ; 
Haustein & Costas, 2015). 
This study focuses on climate change to identify who is engaging with research on Twitter. 
It aims to contribute to the discussion about who tweets about scientific research and the 
definition of user categories. More specifically, we aim to identify non-academic actors to 
understand the practices and context in which the public engages with scientific papers 
on social media. As climate change is a—or the—issue that involves a variety of 
stakeholders—researchers, governmental institutions, science communicators, NGOs—
and is highly relevant to society as a whole, we assume a particularly high engagement by 
the public (IPCC, 2014). Climate change research therefore is a suitable topic to analyze 
non-academic users involved in the communication of research on Twitter. 
Data and methods 
Investigating how climate change research is communicated on Twitter, we built a dataset 
including 2015 and 2016 papers indexed in the Web of Science (WoS) that contained the 
keywords “climate change”, “global warming” or “IPCC” in the title or abstract. Though 
this basic query does not retrieve all publications related to climate change, it provides a 
significant corpus of papers that are directly related to climate research. Our aim was to 
increase precision by accepting lower recall. The publication years were chosen because 
they cover the period before and after the Paris Agreement1, a crucial moment for the 
public understanding of climate change issues. A total of 19 546 publications were 
identified. 
The title is the essential metadata to determine a paper’s relevance and since it also 
frequently appears in the tweet linking to it (Thelwall et al., 2013), it is highly visible to 
Twitter users. We therefore assume that articles, whose titles contain the above 
mentioned keywords, are both more relevant to climate change research and highly 
shared in tweets discussing climate change. The subset of articles containing “climate 
change”, “global warming” or “IPCC” in the title amounts to 4 719 documents. 
Twitter activity and user metrics were compared for both the larger dataset - keywords 
in title or abstract - and the subset of articles containing them in titles only. Tweets were 
collected for each of the 19 546 articles by cross-referencing the information gathered 
from WoS with the Altmetric database via the digital object identifier (DOI). The Twitter 
dataset amounts to a total of 134 212 tweets and 71 166 retweets sent by and 54 229 
unique users linking to 10 032 papers about climate research. Metadata about tweeted 
papers, tweets and user data including Twitter handle, user name, URL and Twitter bio, 
country information and number of followers were collected from Altmetric. Computed 
metrics include the number of papers tweeted, number of tweets, Twitter coverage, 
Twitter density (i.e., number of tweets per paper) and intensity (i.e., number of tweets 
per tweeted paper), number of users, user density (i.e., number of users per document) 
and intensity (i.e., number of users per tweeted document), number of papers retweeted, 
retweet coverage, share of retweets, retweet density (i.e., number of retweets per 
paper), retweet intensity (i.e number of retweets per tweeted document)  as well as the 
timespan between first and last tweet, date of first and last tweet (Haustein, 2018). 
                                                        
1 https://unfccc.int/process-and-meetings/the-paris-agreement/the-paris-agreement 
Preliminary results 
Slightly more than half of the 19 546 climate change articles were shared on Twitter (Table 
1), which exceeds the Twitter coverage of all disciplines (36%; Haustein, 2018) as well as 
Biology (37%), Earth and Space Science (29%) and Social Sciences (39%), but is comparable 
for the percentage found in Health sciences (59%). Although Twitter coverage was only 
slightly higher for papers with climate change keywords in the title (Table 1), their Twitter 
and user density, and thus the average number of tweets and users, was higher than for 
all climate change publications. Twitter density and intensity were also considerably 
higher for climate change papers than all WoS articles published in 2015 (Haustein, 2018). 
This supports our hypothesis that climate change research is particularly relevant and 
receives larger attention on Twitter than other fields of research.  
 
Table 1. Overview of metrics for papers, tweets and users for papers published in 2015 and 2016 for both datasets –   
Top : keywords in titles or abstracts ; Bottom : keywords only in titles. 
 
Table 2 lists user information for the five accounts sharing the largest number of climate 
change research articles on Twitter. These users have all been sharing at least 148 climate 
change articles in 149 tweets during a period of almost 2.5 years. The top 5 includes two 
users, who can be identified as individuals (@geschichtenpost, AGWobserver), two bots 
(@Climate_Papers, @geomatlab) and a university (@Kings_Cambridge). As captured by 
Altmetrics at the time of tweeting, users had between 132 and 967 followers. On average, 
each user seems to tweet each paper once, as indicated by a Twitter intensity close to 1. 
 
 
 
 
 
 
All journals (titles 
and abstracts) 
Papers Twitter 
coverage 
Tweets Twitter 
density 
Twitter 
intensity 
Users User 
density 
User 
intensity 
 19 546 51.33% 134 212 6.87 13.38 54 923 2.81 5.47 
 Papers 
tweeted 
Papers w 
RTs 
RT 
Coverage 
Number 
of RTs 
Share of 
RTs 
RT 
Density 
RT 
Intensity RT Users 
 10 032 5 851 58.32% 77 116 57.50% 3.95 7.69 39 882 
All journals (titles) Papers Twitter 
coverage 
Tweets Twitter 
density 
Twitter 
intensity 
Users User 
density 
User 
intensity 
 4 719 55.52% 41 019 8.69 15.66 21 963 4.65 8.38 
 Papers 
tweeted 
Papers w 
RTs 
RT 
Coverage 
Number 
of RTs 
Share of 
RTs 
RT 
Density 
RT 
Intensity RT Users 
 2 620 1 595 60.88% 23 791 58% 5.04 9.08 15 553 
Table 2. Examples of Twitter user data for the five users with the most tweets linking to a climate change paper. 
Twitter  
handle 
 
User name Twitter bio Followers Tweeted 
papers 
Tweets Tweet 
span 
(in days) 
geschichtenpost Oliver Bothe（￣□￣；） 
#OcAt #pages2k #Hydro #Palmod  
@hzg_de Dad-in-training since 
9/16. Sarcasm, Cynicism, views. 
@eclatmag. Also @OlBothe. 
Welcomes new challenges. 
Aaaaaaahhhhhhhhh 
967 322 338 1,172 
Kings_Cambridge Climate Change 
King’s College #ClimateChange 
Resources & Bibliography. *The 
views expressed on this site do 
not necessarily reflect those of 
King’s College, Cambridge* 
751 231 289 1,043 
Climate_Papers Climate Sci Papers Automated climate science papers 132 238 237 879 
geomatlab POPapers 
PhysicalOceanography Papers 
auto-shared: ARMS NPG JC JPO 
GRL JGR PO JMS OD CSR DSR1 
DSR2 JFM DAO OM OS TA    
Powered by RSS2Twitter@IFTTT. 
Contact @chouj 
353 155 160 910 
AGWobserver Ari Jokimäki 
Climate science hobbyist 
tweeting mostly on new research 
papers. 
821 148 149 1,245 
 
Outlook and future research 
We propose to analyze the Twitter bios applying a codebook allowing for the 
identification of non-exclusive (i.e., overlapping) categories of users. Our challenge is to 
extract keywords (e.g., “Dad-in-training”, “hobbyist”) and create a codebook which helps 
to classify users outside the scientific community. Building on previous work by Haustein 
et al. (2016c) and Haustein (2018), the codebook will focus on the identification of 
accounts maintained by researchers, journals and publishers, universities, NGOs, bots and 
lay users by accounting for the fact that an account may fall into more than one of these 
categories. 
We expect that this classification will help to distinguish academic tweets from those 
involving the general public. This will help to improve scholarly Twitter metrics by 
distinguishing between different types of users and levels of engagement. 
 
References 
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personal and professional impressions on Twitter (Dissertation). Indiana University, Bloomington, IN, USA. 
Retrieved from http://www.tdbowman.com/pdf/2015_07_TDBowman_Dissertation.pdf 
Haustein, S. (2018). Scholarly Twitter Metrics. In W. Glänzel, H.F. Moed, U. Schmoch, & M. Thelwall (Eds.), 
Handbook of Quantitative Science and Technology Research, Springer. 40 pages. Retrieved from 
https://arxiv.org/abs/1806.02201v2 
Haustein, S., Bowman, T. D., & Costas, R. (2016a). Interpreting “altmetrics”: viewing acts on social media 
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A climate of sharing : Who are the users engaging with climate research on Twitter?

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A climate of sharing : Who are the users engaging with climate research on Twitter?

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