Stanford University’s Emily Grubert and Anne Siders recently conducted a broad review of the benefit of incorporating computational text mining and analysis tools in social and humanities studies.
The pair set out to demonstrate that digital tools are useful when searching for patterns at very different scales and particularly relevant in environmental studies.
The review used topic modelling to examine how the field of life-cycle assessment has evolved. The study found that over the last 20 years there have been more LCAs focused on climate change at the expense of those concerned with other impacts.
The study used collocation and network analysis to assess empirical fieldwork on the adaptive capacity of social systems to climate change. This meant the researchers could analyse information at a micro-scale not visible to human readers, picking up on which of 165 determinants of adaptive capacity occurred in the same texts and how these texts were linked. The results, Grubert and Siders write, raise questions about assumptions and theories currently held, consciously or unconsciously, by researchers in the field and inform the development of a new mechanism-based model of adaptive capacity.
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