Evaluating the computational (“Big Data”) turn in studies of media coverage of climate change

Abstract

Machine-assisted big data (MABD) research is enabling quantitative studies of large-scale social phenomena, including societal responses to climate change.The rise of MABD science is causing both enthusiasm and concerns. Reviewing prominent criticisms of MABD and their relevance for MABD explorations of macro-structural factors shaping media coverage of climate change, this article finds that the quality and contributions of such studies depend on avoiding common pitfalls. The review focuses specifically on MABD studies' attempts to identify and make sense of correlations-or lack thereof-between climate vulnerability and climate coverage in different countries. The review draws on insights from a single, nationally focused, context-attentive, and relatively more qualitative "small data" study in the Global South (Brazil) to shed critical light on assumptions, claims, and policy recommendations made based on the computer-assisted macro-studies. The review illustrates why more narrowly focused and qualitative small data studies are complementary and indispensable. Besides providing vital understanding of causal relationships that elude MABD studies, more narrowly focused and context-sensitive qualitative studies can foster understanding of the consequential mediating roles of place-specific meaning-making and political strategizing in how climate and weather phenomena are framed by social actors and mass media in particular places. These are dimensions that escape the Big Data quantitative methods, but that are vital to sound policy advice, as illustrated by the Small Data research from Brazil.

Steering signification for sustainability

“…Critical social studies of science and technology (STS) remain under-tapped for their strength in fostering meta-level understanding and, as such, a meta-science of sorts (Jasanoff, 1996) of great importance for global environmental research and policy (Lahsen, 2024a). The field of STS offers and encourages reflection on, and redesign of, how science and technology, including communications systems and related policies, affect our societies, with emphasis on understanding and countering oppressive power and on implementing participatory arrangements in service of collective interests (Kreimer & Vessuri, 2018;Stirling, 2003).…”

Community and identity in environmental activism on Twitter: A discourse-based approach

“…Research on social media and environmental activism has been growing with many studies adopting quantitative and often also deductive approaches to study the large volumes of mainly textual content, which has led to recommendations to conduct more qualitative studies and include non-textual content in future research (see e.g., Pearce et al 2019). This growth in quantitative analyses of social media and environmental activism is not unexpected when seen in the broader context of a quantitative, "Big Data" turn in studies of climate change and the media (Lahsen 2021) and the prestige that quantitative approaches have historically enjoyed over other ways of analysis (Daston and Galison 1992). In what follows, we review examples of this type of research without aiming to be exhaustive, but instead to show the types of questions that are typically explored with the aid of such approaches.…”

Computational methods for the analysis of climate change communication: Towards an integrative and reflexive approach

“…For the context of climate change communication, existing work has been reflexive by critically discussing shortcomings of computational advances and how not to use them, often for the context of specific studies and questions (e.g., Lahsen, 2021). However, we are not aware of work providing concrete guidance on when and how to apply these methods in a more integrative manner and beyond selected questions.…”

“…However, we are not aware of work providing concrete guidance on when and how to apply these methods in a more integrative manner and beyond selected questions. Taking the work by Lahsen (2021) as a starting point and in line with arguments by Grundmann (2021) that computational methods “need to be aligned with theoretical perspectives […] in order to advance research in this field” (p. 395), we propose a reflexive and integrative perspective for computational methods: We reflect strengths and weaknesses of computational methods for studying climate change communication. Related to these, we also propose guidance on how computational advances could be integrated via theory —including when to opt against using them.…”

“…As communication scholars, we focus on a specific strand of this discussion: the analysis of large‐scale text corpora from social media platforms (Pearce et al, 2019) or news media (Grundmann & Scott, 2014; Hase et al, 2021; Kirilenko & Stepchenkova, 2012) via automated content analysis. In the field of climate change communication, NLP approaches have recently faced some criticism (Grundmann, 2021), often with a focus on specific questions and studies (Lahsen, 2021). Taking these discussions as a starting point, we (a) critically reflect upon strengths and weakness of NLP approaches beyond single studies or questions, and (b), by relying on theory, provide concrete and constructive guidance on when and how to (not) integrate these methods .…”