News media attention in Climate Action: latent topics and open access
Artikel i vetenskaplig tidskrift, 2021

In this study we investigated whether open access could assist the broader dissemination of scientific research in Climate Action (Sustainable Development Goal 13) via news outlets. We did this by comparing (i) the share of open and non-open access documents in dif-ferent Climate Action topics, and their news counts, and (ii) the mean of news counts for open access and non-open access documents. The data set of this study comprised 70,206 articles and reviews in Sustainable Development Goal 13, published during 2014–2018, retrieved from SciVal. The number of news mentions for each document was obtained from Altmetrics Details Page API using their DOIs, whereas the open access statuses were obtained using Unpaywall.org. The analysis in this paper was done using a combination of (Latent Dirichlet allocation) topic modelling, descriptive statistics, and regression anal-ysis. The covariates included in the regression analysis were features related to authors, country, journal, institution, funding, readability, news source category and topic. Using topic modelling, we identified 10 topics, with topics 4 (meteorology) [21%], 5 (adaption, mitigation, and legislation) [18%] and 8 (ecosystems and biodiversity) [14%] accounting for 53% of the research in Sustainable Development Goal 13. Additionally, the results of regression analysis showed that while keeping all the variables constant in the model, open access papers in Climate Action had a news count advantage (8.8%) in comparison to non-open access papers. Our findings also showed that while a higher share of open access documents in topics such as topic 9 (Human vulnerability to risks) might not assist with its broader dissemination, in some others such as topic 5 (adaption, mitigation, and legisla-tion), even a lower share of open access documents might accelerate its broad communica-tion via news outlets.

Altmetrics

News media

SDG 13 (Climate Action)

Open access

Topic modelling

Författare

Tahereh Dehdarirad

Chalmers, Vetenskapens kommunikation och lärande, Forskarstöd, bibliometri och rankning

Kalle Karlsson

Högskolan i Borås

Scientometrics

0138-9130 (ISSN) 1588-2861 (eISSN)

Ämneskategorier

Medie- och kommunikationsvetenskap

Datavetenskap (datalogi)

DOI

10.1007/s11192-021-04095-7

Mer information

Skapat

2021-07-14