Data Science for Economics and Finance Methodologies and Applications

dc.contributor.authorSergio Consoli
dc.contributor.authorDiego Reforgiato Recupero
dc.date.accessioned2026-02-09T21:08:54Z
dc.date.available2026-02-09T21:08:54Z
dc.date.issued2021
dc.descriptionLibro electrónico
dc.description.abstractThis open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.
dc.identifier.isbn978-3-319-69623-872
dc.identifier.otherhttps://doi.org/10.1007/978-3-030-66891-4
dc.identifier.urihttps://link.springer.com/openurl?genre=book&isbn=978-3-030-66891-4
dc.identifier.urihttp://bibliovirtual.umar.mx:4000/handle/123456789/1701
dc.language.isoen_US
dc.publisherSpringer International Publishing
dc.titleData Science for Economics and Finance Methodologies and Applications
dc.typeBook
eperson.firstnamenombre
person.jobTitletrabajo

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