000151721 001__ 151721
000151721 005__ 20250319155218.0
000151721 0247_ $$2doi$$a10.1016/j.envsoft.2025.106382
000151721 0248_ $$2sideral$$a143229
000151721 037__ $$aART-2025-143229
000151721 041__ $$aeng
000151721 100__ $$0(orcid)0000-0002-4854-8062$$aLópez-Otal, Miguel$$uUniversidad de Zaragoza
000151721 245__ $$aSeqIA: A Python framework for extracting drought impacts from news archives
000151721 260__ $$c2025
000151721 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151721 5203_ $$aDrought is a hazard that causes great economic, ecological, and human loss. With an ever-growing risk of climate change, their frequency and magnitude are expected to increase. While there are many indices and metrics available for the analysis of droughts, assessing their impacts represents one of the best ways to understand their magnitude and extent. However, there are no systematic records outlining these impacts. To help in their ongoing creation, we present a software framework that leverages raw newspaper articles, identifies any drought-related ones, and automatically classifies them according to a set of socioeconomic impacts. The information is provided to the user in a structured format, including geographical coordinates and their date of reporting. Our approach employs state-of-the-art Transformer-based Natural Language Processing (NLP) techniques, which achieve great accuracy. We currently support newspaper articles in the Spanish language within Spain, but our framework can be expanded to other countries and languages.
000151721 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2020-113903RB-I00$$9info:eu-repo/grantAgreement/EUR/MICINN/FEDER/TED2021-129152B-C41$$9info:eu-repo/grantAgreement/EUR/MICINN/FEDER/TED2021-129152B-C42$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-108589RA-I00$$9info:eu-repo/grantAgreement/ES/MINECO/RYC2019-028112-I
000151721 540__ $$9info:eu-repo/semantics/embargoedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000151721 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000151721 700__ $$0(orcid)0000-0003-3085-7040$$aDomínguez-Castro, Fernando
000151721 700__ $$aLatorre, Borja
000151721 700__ $$aVela-Tambo, Javier
000151721 700__ $$0(orcid)0000-0001-6452-7627$$aGracia, Jorge$$uUniversidad de Zaragoza
000151721 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000151721 773__ $$g187 (2025), 106382 [19 pp.]$$pEnviron. model. softw.$$tENVIRONMENTAL MODELLING & SOFTWARE$$x1364-8152
000151721 8564_ $$s702949$$uhttps://zaguan.unizar.es/record/151721/files/texto_completo.pdf$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2027-02-24
000151721 8564_ $$s1641481$$uhttps://zaguan.unizar.es/record/151721/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2027-02-24
000151721 909CO $$ooai:zaguan.unizar.es:151721$$particulos$$pdriver
000151721 951__ $$a2025-03-19-14:21:30
000151721 980__ $$aARTICLE