Evaluating the computational (“Big Data”) turn in studies of media coverage of climate change
Datos Bibliográficos
| ID | 12929565 |
|---|---|
| Autores | Myanna Lahsen (0000-0001-5225-2048, Linköping University, autor de correspondencia) |
| Año | 2021 |
| Volumen | 13 |
| Número | 2 |
| Fecha de publicación | 2021-12-26 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Wiley Interdisciplinary Reviews Climate Change (JOURNAL) |
| Identificadores de la revista | ISSN: 1757-7780 • E-ISSN: 1757-7799 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/wcc.752 |
| OpenAlex | W4200149680 |
| Idioma | EN |
| Citas recibidas | 5 |
| Referencias citadas | 33 |
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
Big data · Climate change · Context (archaeology · Data science · Enthusiasm · Geography · Meaning (existential · Political science · Public relations · Qualitative property · Social media · Sociology · Vulnerability (computing · Atmospheric and Environmental Gas Dynamics · Climate Change Communication and Perception · Computer Science · Psychology · Social Psychology · Sustainability and Climate Change Governance · Ecology
The Data Revolution
Big Data and Management
Critical analysis of Big Data challenges and analytical methods
Dividing climate change
Social media for large studies of behavior
Climate change in Peruvian newspapers
Leveraging Digital Disruptions for a Climate-Safe and Equitable World
Should AI be Designed to Save Us From Ourselves
Assessing Artificial Intelligence for Humanity
Who Speaks for the Climate
Faster than the speed of print
The Age of Surveillance Capitalism
Media coverage of climate change
Geography and the future of big data, big data and the future of geography
Politics of attributing extreme events and disasters to climate change
Problems with making and governing global kinds of knowledge☆
Media attention for climate change around the world
Nationalizing a global phenomenon
Seductive Simulations? Uncertainty Distribution Around Climate Models
Antifragile
Leviathan and the Air-Pump
The Image of Objectivity
What Social Science Must Learn From the Humanities
Conflicting Climate Change Frames in a Global Field of Media Discourse
| Obras citantes distintas | 5 |
|---|---|
| Citas por año | 1,25 |
| Intervalo de citas | 2022 - 2024 (3) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 5 |