150564 20260121150013.0 doi 10.1111/itor.13568 sideral 142631 ART-2025-142631 eng Aguarón, J. Universidad de Zaragoza (orcid)0000-0003-3138-7597 Mood and emotion assessment for risk reduction of pandemic spread through passenger air transport: a DSS applied to the COVID-19 in the case of Spain 2025 Access copy available to the general public Unrestricted This paper presents a decision support system (DSS) for sentiment analysis of Spanish texts based on lexicons. The information provided by this DSS, named Spanish Sentiment Analysis‐DSS (SSA‐DSS), is employed to assess the social impacts considered in an external software module (RRPS‐PAT) centered on risk reduction of pandemic spread through passenger air transport. RRPS‐PAT is a complex multiobjective optimization module simultaneously addressing different conflicting objectives, including epidemiological, economic, and social aspects. This allows more effective and realistic decisions to be made. The specificity and novelty of the problem suggest the use of lexicon‐based approaches because there is no prior information about the problem to train machine learning–based approaches. The SSA‐DSS covers the entire process from the incorporation of texts, particularly tweets, to be analyzed, the application of preprocessing and cleaning tools, the selection of lexicons (general, context, and emoji lexicons) to be used and their possible modification, to the visualization of results and their exportation to other software tools. This paper contemplates, apart from the RRPS‐PAT module, the connection with a social network analysis tool (Gephi) that complements the information provided by SSA‐DSS with the identification of social leaders. The usefulness and functionalities of SSA‐DSS are illustrated by means of an example related to the evolution of societal mood in Spain during the COVID‐19 pandemic. info:eu-repo/grantAgreement/ES/AEI/PID2021-122209OB-C31 info:eu-repo/grantAgreement/ES/AEI/RED2022-134540-T info:eu-repo/grantAgreement/ES/DGA/LMP 35-21 info:eu-repo/grantAgreement/ES/MICINN/PID2022-139863OB-I00 info:eu-repo/semantics/openAccess by-nc-nd https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es 2.9 2024 MANAGEMENT 198 / 420 = 0.471 2024 Q2 T2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 37 / 106 = 0.349 2024 Q2 T2 0.993 2024 Business and International Management 2024 Q1 Computer Science Applications 2024 Q1 Strategy and Management 2024 Q1 Management Science and Operations Research 2024 Q1 Management of Technology and Innovation 2024 Q2 7.8 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Altuzarra, A. Universidad de Zaragoza (orcid)0000-0002-0117-7655 Aznar, R. Escobar, M.T. Universidad de Zaragoza (orcid)0000-0003-4419-1905 Jiménez-Martín, A. Mateos, A. Moreno-Díaz, A. Moreno-Jiménez, J.M. Universidad de Zaragoza (orcid)0000-0002-5037-6976 Moreno-Loscertales, C. Universidad de Zaragoza Muerza, V. Universidad de Zaragoza (orcid)0000-0002-2405-4375 Navarro, J. Universidad de Zaragoza (orcid)0000-0001-6148-0667 Sarango, A. Turón, A. Universidad de Zaragoza (orcid)0000-0002-8807-8958 Vargas, L.G. 1007 610 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Medicina 4014 623 Universidad de Zaragoza Dpto. Economía Aplicada Área Métodos Cuant.Econ.Empres 32, 4 (2025), 1918-1949 Int. trans. oper. res. INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 0969-6016 4075425 http://zaguan.unizar.es/record/150564/files/texto_completo.pdf Versión publicada 2519473 http://zaguan.unizar.es/record/150564/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:150564 articulos driver 2026-01-21-14:58:47 ARTICLE