In this work we analyse the evolution of the vulnerability concept in the research streams of climate change adaptation (CCA) and disaster risk reduction (DRR). We combine a traditional literature review with data mining procedures applied to bibliographic databases to reconstruct the history of the concept within various research topics, showing its evolution and convergences over time. To do that, we integrate different methods combining machine learning algorithms with network and cluster analyses to examine a set of 3757 articles, analysing their distinctive features and similarities on the basis of their contents as well as co-authorships. Bibliometric analyses enable the identification of different communities of articles, pinpointing key papers and authors, while literature review makes it possible to assess the concept of vulnerability evolved within and beyond research communities and scientific networks. Moreover, this work examines the role played by documents published by UN institutions (UNDRO, UNISDR, IPCC) in contributing to the evolution of vulnerability and related concepts. Results show that signs of convergence are evident between the two research streams, and that the IPCC reports have played a major role in proposing solutions for unifying definitions of vulnerability. We observe that the phases of preparation of the IPCC reports are very rich in methodological and terminological developments, while after publication, the literature shows evident signs of propagation of the proposed concepts. The DRR research stream developed before the research stream on CCA, but the latter flourished rapidly and became much larger in terms of number of publications. Nevertheless, in terms of contents, adaptation studies and the IPCC have shown increasing adoption of the concepts developed within the disaster research stream, in particular with regard to the interpretation of vulnerability as one of the dimensions of risk.

Vulnerabilities-bibliometric analysis and literature review of evolving concepts

GIUPPONI, Carlo;BISCARO, CLAUDIO
2015-01-01

Abstract

In this work we analyse the evolution of the vulnerability concept in the research streams of climate change adaptation (CCA) and disaster risk reduction (DRR). We combine a traditional literature review with data mining procedures applied to bibliographic databases to reconstruct the history of the concept within various research topics, showing its evolution and convergences over time. To do that, we integrate different methods combining machine learning algorithms with network and cluster analyses to examine a set of 3757 articles, analysing their distinctive features and similarities on the basis of their contents as well as co-authorships. Bibliometric analyses enable the identification of different communities of articles, pinpointing key papers and authors, while literature review makes it possible to assess the concept of vulnerability evolved within and beyond research communities and scientific networks. Moreover, this work examines the role played by documents published by UN institutions (UNDRO, UNISDR, IPCC) in contributing to the evolution of vulnerability and related concepts. Results show that signs of convergence are evident between the two research streams, and that the IPCC reports have played a major role in proposing solutions for unifying definitions of vulnerability. We observe that the phases of preparation of the IPCC reports are very rich in methodological and terminological developments, while after publication, the literature shows evident signs of propagation of the proposed concepts. The DRR research stream developed before the research stream on CCA, but the latter flourished rapidly and became much larger in terms of number of publications. Nevertheless, in terms of contents, adaptation studies and the IPCC have shown increasing adoption of the concepts developed within the disaster research stream, in particular with regard to the interpretation of vulnerability as one of the dimensions of risk.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3667085
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