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Big Data sources and methods for social and economic analyses

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Big Data sources and methods for social and economic analyses

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dc.contributor.author Blazquez, Desamparados es_ES
dc.contributor.author Domenech, Josep es_ES
dc.date.accessioned 2018-07-16T06:50:37Z
dc.date.available 2018-07-16T06:50:37Z
dc.date.issued 2018 es_ES
dc.identifier.issn 0040-1625 es_ES
dc.identifier.uri http://hdl.handle.net/10251/105831
dc.description.abstract [EN] The Data Big Bang that the development of the ICTs has raised is providing us with a stream of fresh and digitized data related to how people, companies and other organizations interact. To turn these data into knowledge about the underlying behavior of the social and economic agents, organizations and researchers must deal with such amount of unstructured and heterogeneous data. Succeeding in this task requires to carefully plan and organize the whole process of data analysis taking into account the particularities of the social and economic analyses, which include the wide variety of heterogeneous sources of information and a strict governance policy. Grounded on the data lifecycle approach, this paper develops a Big Data architecture that properly integrates most of the non-traditional information sources and data analysis methods in order to provide a specifically designed system for forecasting social and economic behaviors, trends and changes. es_ES
dc.description.sponsorship This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under Grant TIN2013-43913-R; and by the Spanish Ministry of Education under Grant FPU14/02386. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Technological Forecasting and Social Change es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Big Data architecture es_ES
dc.subject Forecasting es_ES
dc.subject Nowcasting es_ES
dc.subject Data lifecycle es_ES
dc.subject Socio-economic data es_ES
dc.subject Non-traditional data sources es_ES
dc.subject Non-traditional analysis methods es_ES
dc.subject.classification ECONOMIA APLICADA es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Big Data sources and methods for social and economic analyses es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.techfore.2017.07.027 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2013-43913-R/ES/EFICIENCIA ECONOMICA EN LA PLANIFICACION Y USO DE INFRAESTRUCTURAS CLOUD/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU2014-02386/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.description.bibliographicCitation Blazquez, D.; Domenech, J. (2018). Big Data sources and methods for social and economic analyses. Technological Forecasting and Social Change. 130:99-113. https://doi.org/10.1016/j.techfore.2017.07.027 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.techfore.2017.07.027 es_ES
dc.description.upvformatpinicio 99 es_ES
dc.description.upvformatpfin 113 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 130 es_ES
dc.relation.pasarela S\342360 es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES


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