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

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. This article is categorized under: Social Status of Climate Change Knowledge > Knowledge and Practice