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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2018-200
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2018-200
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 26 Jul 2018

Research article | 26 Jul 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Natural Hazards and Earth System Sciences (NHESS) and is expected to appear here in due course.

Climate risks, digital media, and big data: following communication trails to investigate urban communities' resilience

Rosa Vicari, Ioulia Tchiguirinskaia, and Daniel Schertzer Rosa Vicari et al.
  • Hydrology Meteorology and Complexity Laboratory, École des Ponts ParisTech, Marne-la-Vallée, Champs-sur-Marne, 77455, France

Abstract. Nowadays, when extreme weather affects an urban area, huge amounts of digital data are spontaneously produced by the population on the Internet. These digital trails can provide an insight on the interactions existing between climate related risks and the social perception of these risks. According to this research big data exploration techniques can be exploited to monitor these interactions and their effect on urban resilience. The experiments presented in this paper show that digital research can bring out the most central issues in the digital media, identify the stakeholders that have the capacity to influence the debate and, therefore, the community attitudes towards an issue. Three corpora of Web communication data have been extracted: press news covering the June 2016 Seine River flood; press news covering the October 2015 Alpes-Maritimes flood; tweets on the 2016 Seine River flood. The analysis of these datasets involves an iteration between manual and automated extraction of hundreds of key terms, network representations based on key terms co-occurrences, automated cluster visualisation based on adjacency matrix, and profiling of social media users. Visual observation of the network coupled to quantitative analysis of its nodes and edges allow obtaining an in-depth understanding of the most prominent topics and actors, as well as of the connections and clusters that these topics and actors tend to form in the journalistic sphere. Through a comparison of the three datasets, it is also possible to observe how these patterns change over time, in different urban areas and in different digital media contexts.

Rosa Vicari et al.
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Rosa Vicari et al.
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Short summary
Nowadays, when extreme weather affects an urban area, huge amounts of digital data are spontaneously produced by the population on the Web. These digital trails can provide an insight on the interactions between climate related risks and the social perception of these risks. The experiments presented in this paper show that big data exploration techniques can bring out the most central issues and actors in the debate and explore how it affects urban resilience.
Nowadays, when extreme weather affects an urban area, huge amounts of digital data are...
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