Climate resilience in Paris: A network representation of online strategic documents released by public authorities
This study proposes to exploit recent advances in data mining techniques to examine the strategies published on the Internet by public authorities and implemented in Paris. We first conducted a qualitative review of strategic documents, released over 15 years. We then used a list of key terms concer...
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Series: | Progress in Disaster Science |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590061719300407 |
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doaj-3aa0edbc4e3440bd9b0bc013f1d5563f2020-11-25T01:51:38ZengElsevierProgress in Disaster Science2590-06172019-10-013Climate resilience in Paris: A network representation of online strategic documents released by public authoritiesRosa Vicari0Ioulia Tchiguirinskaia1Bruno Tisserand2Daniel Schertzer3Hydrology Meteorology and Complexity Laboratory, École des Ponts ParisTech, France; Corresponding author at: 6–8 Avenue B. Pascal, Marne–la–Vallée, Champs–sur–Marne 77455, Hydrology Meteorology and Complexity Laboratory, École des Ponts ParisTech, France.Hydrology Meteorology and Complexity Laboratory, École des Ponts ParisTech, FranceVeolia Research and Innovation, FranceHydrology Meteorology and Complexity Laboratory, École des Ponts ParisTech, FranceThis study proposes to exploit recent advances in data mining techniques to examine the strategies published on the Internet by public authorities and implemented in Paris. We first conducted a qualitative review of strategic documents, released over 15 years. We then used a list of key terms concerning flood risk management to compute a semantic network and identify clusters of terms that tend to appear in similar contexts. The analysis reveals an evolution of how policy and decision-making processes are depicted on the Web. The proposed methodology can be reproduced in other cities facing climate risks. Keywords: Urban resilience, Climate risks, Network representationhttp://www.sciencedirect.com/science/article/pii/S2590061719300407 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rosa Vicari Ioulia Tchiguirinskaia Bruno Tisserand Daniel Schertzer |
spellingShingle |
Rosa Vicari Ioulia Tchiguirinskaia Bruno Tisserand Daniel Schertzer Climate resilience in Paris: A network representation of online strategic documents released by public authorities Progress in Disaster Science |
author_facet |
Rosa Vicari Ioulia Tchiguirinskaia Bruno Tisserand Daniel Schertzer |
author_sort |
Rosa Vicari |
title |
Climate resilience in Paris: A network representation of online strategic documents released by public authorities |
title_short |
Climate resilience in Paris: A network representation of online strategic documents released by public authorities |
title_full |
Climate resilience in Paris: A network representation of online strategic documents released by public authorities |
title_fullStr |
Climate resilience in Paris: A network representation of online strategic documents released by public authorities |
title_full_unstemmed |
Climate resilience in Paris: A network representation of online strategic documents released by public authorities |
title_sort |
climate resilience in paris: a network representation of online strategic documents released by public authorities |
publisher |
Elsevier |
series |
Progress in Disaster Science |
issn |
2590-0617 |
publishDate |
2019-10-01 |
description |
This study proposes to exploit recent advances in data mining techniques to examine the strategies published on the Internet by public authorities and implemented in Paris. We first conducted a qualitative review of strategic documents, released over 15 years. We then used a list of key terms concerning flood risk management to compute a semantic network and identify clusters of terms that tend to appear in similar contexts. The analysis reveals an evolution of how policy and decision-making processes are depicted on the Web. The proposed methodology can be reproduced in other cities facing climate risks. Keywords: Urban resilience, Climate risks, Network representation |
url |
http://www.sciencedirect.com/science/article/pii/S2590061719300407 |
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