Computational methods for climate change frame analysis: Techniques, critiques, and cautious ways forward

Abstract

AbstractFrame analysis is a popular methodological paradigm to investigate how climate change is reported in the media, how it is negotiated by political actors, and perceived by publics. Its scope of application extends across various academic disciplines and transcends traditional boundaries of research such as those between quantitative and qualitative methods. Recent transformations of the media landscape have a strong influence on how frame analysis is conducted and how it is used to investigate climate change communication. Online data mining and computational methods have now become increasingly mainstream to investigate discursive elements in online media. Scholars have highlighted the potential, but also the risks associated with sophisticated computational methods, such as machine learning, increasingly used in the context of frame analysis. This advanced review gathers the scientific literature on computational frame analysis for analyzing climate change communication and discusses ways of dealing with associated risks and caveats by incorporating ideas from Science & Technology Studies (STS) and other stances of critical scholarship. Recommended ways forward include combining methods, practicing theoretical interdisciplinarity, infrastructuring reflexivity in research constellations, and embracing transparency, documentation, and accessibility of methods.This article is categorized under: The Social Status of Climate Change Knowledge > Sociology/Anthropology of Climate Knowledge Perceptions, Behavior, and Communication of Climate Change > Communication Climate, History, Society, Culture > Technological Aspects and Ideas