Defly Compass Trend Analysis Methodology: Quantifying Trend Detection to Improve Foresight in Strategic Decision Making

dc.contributor.affiliationDepartamento de Comunicación Audiovisual, Documentación e Historia del Arte
dc.contributor.affiliationFacultad de Administración y Dirección de Empresas
dc.contributor.affiliationDepartamento de Matemática Aplicada
dc.contributor.affiliationInstituto Universitario de Matemática Pura y Aplicada
dc.contributor.affiliationEscuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos
dc.contributor.authorLópez Bordao, Mabeles_ES
dc.contributor.authorFerrer Sapena, Antonia
dc.contributor.authorReyes Pérez, Carlos A.es_ES
dc.contributor.authorSánchez Pérez, Enrique Alfonso
dc.contributor.funderGeneralitat Valencianaes_ES
dc.date.accessioned2026-05-28T10:55:50Z
dc.date.available2026-05-28T10:55:50Z
dc.date.issued2025-07-14es_ES
dc.description.abstract[EN] We present a new method for trend analysis that integrates traditional foresight techniques with advanced data processing and artificial intelligence. It addresses the challenge of analyzing large volumes of information while preserving expert insight. The hybrid methodology combines computational analysis with expert validation across four phases: literature review, information systematization, trend identification, and analysis. Tools like Voyant Tools 2.6.18 and NotebookLMare used for semantic and statistical exploration. Among them, we highlight the use of the Defly Compass tool, a natural language processing tool based on semantic projections and developed by our team. The method produces mixed results, including both conceptual conclusions and quantifiable, reproducible outcomes adaptable to diverse contexts. Comparative case studies in agriculture, education, and public health identified key patterns within and across sectors. Cross-domain validation revealed universal trends such as digital infrastructure, data integration, and equity. Designed for accessibility, the method enables small, non-specialized teams to combine computational tools with expert knowledge for strategic decision making in complex environments.es_ES
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationLópez Bordao, M.; Ferrer Sapena, Antonia; Reyes Pérez, CA.; Sánchez Pérez, Enrique Alfonso (2025). Defly Compass Trend Analysis Methodology: Quantifying Trend Detection to Improve Foresight in Strategic Decision Making. Information. 16(7). https://doi.org/10.3390/info16070605es_ES
dc.description.issue7es_ES
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dc.description.sponsorshipThis research was funded by Generalitat Valenciana (Spain), grant number PROMETEO 2024 CIPROM/2023/32.es_ES
dc.description.volume16es_ES
dc.identifier.doi10.3390/info16070605es_ES
dc.identifier.eissn2078-2489es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/235487
dc.languageIngléses_ES
dc.publisherMDPI AGes_ES
dc.relation.ispartofInformationes_ES
dc.relation.pasarelaS\559909es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/GVA//CIPROM%2F2023%2F32/es_ES
dc.relation.publisherversionhttps://doi.org/10.3390/info16070605es_ES
dc.rightsReconocimiento (by)es_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectTrendes_ES
dc.subjectForecastinges_ES
dc.subjectFutureses_ES
dc.subjectNLPes_ES
dc.subjectDefly Compasses_ES
dc.subjectSemantic projectiones_ES
dc.titleDefly Compass Trend Analysis Methodology: Quantifying Trend Detection to Improve Foresight in Strategic Decision Makinges_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
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