Automatized Drought Impact Detection Using Natural Language Processing

Sodoge, Jan; Brito, Mariana Madruga de; Kuhlicke, Christian

doi:10.1007/s35147-022-1008-7

Cited by 4 publications

(2 citation statements)

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“…To extract the geographical locations mentioned in each article, we followed the three-step method proposed by Sodoge et al (Sodoge et al, 2022) (see Supplementary Fig. S2).…”

Section: Location Extractionmentioning

confidence: 99%

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Comprehensive assessment of flood socioeconomic impacts through text-mining

Brito,

Sodoge,

Kreibich

et al. 2024

Preprint

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In July 2021, Germany experienced its costliest riverine floods in history, with over 189 fatalities and a staggering \euro33 billion in damages. Following this event, news outlets widely disseminated information on the flood’s aftermath. Here, we demonstrate how newspaper data can be instrumental in the assessment of flood socioeconomic impacts often overlooked by conventional methods. Using natural language processing tools on 14,888 unique newspaper articles, we estimate the impacts of the 2021 flood on various sectors and critical infrastructure, including water contamination, mental health, and tourism. Our results revealed severe and lasting impacts in the Ahr Valley, even months after the event. At the same time, we identified smaller-scale yet widespread impacts across Germany, which are typically overlooked by existing impact databases. Our approach advances current research by systematically examining indirect and intangible flood impacts over large areas. This underscores the value of leveraging complementary text data to provide a more comprehensive picture of flood impacts.

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“…To extract the geographical locations mentioned in each article, we followed the three-step method proposed by Sodoge et al (Sodoge et al, 2022) (see Supplementary Fig. S2).…”

Section: Location Extractionmentioning

confidence: 99%

“…The capabilities of the three-step location extraction method were evaluated in detail in previous research (Sodoge et al, 2022). To evaluate its performance in this study, we drew a random sample of 50 unique newspaper articles.…”

Section: Location Extractionmentioning

confidence: 99%