Vulnerable voices: using topic modeling to analyze newspaper coverage of climate change in 26 non-Annex I countries (2010–2020)

Abstract

News media influence how climate change is represented, understood, and discussed in the public sphere. To date, media and climate change research has primarily focused on Annex I countries, or treated non-Annex I countries as a homogenous bloc, despite the global nature of climate change and its geographically uneven impacts. This study uses a mixed-method approach, combining machine learning (topic modeling), econometrics, and qualitative analyses, to investigate newspaper coverage of climate change in 26 non-Annex I countries. We compiled a dataset of 95 216 news articles (dated between 2010 and 2020 from 50 sources) in 26 lower-middle and upper-middle income non-Annex I countries. In line with previous research results, we find that most common topics represented are international governance of climate change, the economics of energy transitions, and the impacts of climate change. Advancing current research understanding, we also demonstrate heterogeneity in coverage between non-Annex I countries and discover that a country’s vulnerability to climate change is positively associated with the diversity of topics (based on an article-level entropy index) portrayed by its domestic news media outlets.