000126354 001__ 126354 000126354 005__ 20241125101140.0 000126354 0247_ $$2doi$$a10.1016/j.ijdrr.2023.103694 000126354 0248_ $$2sideral$$a133800 000126354 037__ $$aART-2023-133800 000126354 041__ $$aeng 000126354 100__ $$0(orcid)0000-0001-6148-0667$$aNavarro, J.$$uUniversidad de Zaragoza 000126354 245__ $$aPress media impact of the Cumbre Vieja volcano activity in the island of La Palma (Canary Islands): A machine learning and sentiment analysis of the news published during the volcanic eruption of 2021 000126354 260__ $$c2023 000126354 5060_ $$aAccess copy available to the general public$$fUnrestricted 000126354 5203_ $$aIn this work we have used as a source of information a large sample of the press articles published during 2021 about the eruption of the Cumbre Vieja volcano in the island of La Palma (Canary Islands). In contraposition, the scientific papers evaluating different facets of natural disasters have preferentially used social networks as a source of information. Herein we have shown how the emotions and sentiments expressed in press media can be efficiently analyzed via AI techniques to better assess the social impact of a disaster at the time it takes place. We have also gauged the usefulness of different classifiers combining sentiment analysis with multivariate statistical analysis and machine learning techniques. By applying this methodology, we were able to classify a newspaper article within a certain time frame of the eruption, and we observed significant differences between local news published in Spanish and those of foreign newspapers written in English. We also found different emotional trajectories of articles by applying the Fourier transform onto the inner “valence” progress along each article narrative time. In addition, there appeared a significant relationship between the surface area occupied by lava and the emotions and sentiments expressed in the articles—many other correlations and causalities could be explored too. The main findings of this research may constitute a helpful resource for a better understanding of the way press media react to volcanic activity, and may guide in public decision-making under different temporal horizons, including the design of improved strategies in the risk reduction domain. 000126354 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttp://creativecommons.org/licenses/by-nc/3.0/es/ 000126354 590__ $$a4.2$$b2023 000126354 592__ $$a1.132$$b2023 000126354 591__ $$aGEOSCIENCES, MULTIDISCIPLINARY$$b34 / 254 = 0.134$$c2023$$dQ1$$eT1 000126354 593__ $$aGeology$$c2023$$dQ1 000126354 591__ $$aWATER RESOURCES$$b25 / 128 = 0.195$$c2023$$dQ1$$eT1 000126354 593__ $$aSafety Research$$c2023$$dQ1 000126354 591__ $$aMETEOROLOGY & ATMOSPHERIC SCIENCES$$b26 / 110 = 0.236$$c2023$$dQ1$$eT1 000126354 593__ $$aGeotechnical Engineering and Engineering Geology$$c2023$$dQ1 000126354 594__ $$a8.7$$b2023 000126354 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000126354 700__ $$aPiña, J. Urias 000126354 700__ $$aMas, F. Magdaleno 000126354 700__ $$aLahoz-Beltra, R. 000126354 7102_ $$14014$$2623$$aUniversidad de Zaragoza$$bDpto. Economía Aplicada$$cÁrea Métodos Cuant.Econ.Empres 000126354 773__ $$g91 (2023), 103694 [19 pp.]$$pInternational journal of disaster risk reduction.$$tInternational Journal of Disaster Risk Reduction$$x2212-4209 000126354 8564_ $$s8220215$$uhttps://zaguan.unizar.es/record/126354/files/texto_completo.pdf$$yVersión publicada 000126354 8564_ $$s1786053$$uhttps://zaguan.unizar.es/record/126354/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000126354 909CO $$ooai:zaguan.unizar.es:126354$$particulos$$pdriver 000126354 951__ $$a2024-11-22-12:02:22 000126354 980__ $$aARTICLE