LEADER 06697nam 22010095 450 001 9910484567403321 005 20230125195910.0 010 $a3-030-66891-6 024 7 $a10.1007/978-3-030-66891-4 035 $a(CKB)5590000000486830 035 $a(DE-He213)978-3-030-66891-4 035 $a(MiAaPQ)EBC6640078 035 $a(Au-PeEL)EBL6640078 035 $a(OCoLC)1257416604 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/70804 035 $a(PPN)258065400 035 $a(EXLCZ)995590000000486830 100 $a20210629d2021 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Science for Economics and Finance $eMethodologies and Applications /$fedited by Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana 205 $a1st ed. 2021. 210 $cSpringer Nature$d2021 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (XIV, 355 p. 56 illus., 44 illus. in color.) 311 $a3-030-66890-8 327 $aData Science Technologies in Economics and Finance: A Gentle Walk-In -- Supervised Learning for the Prediction of Firm Dynamics -- Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting -- Machine Learning for Financial Stability -- Sharpening the Accuracy of Credit Scoring Models with Machine Learning Algorithms -- Classifying Counterparty Sector in EMIR Data -- Massive Data Analytics for Macroeconomic Nowcasting -- New Data Sources for Central Banks -- Sentiment Analysis of Financial News: Mechanics and Statistics -- Semi-supervised Text Mining for Monitoring the News About the ESG Performance of Companies -- Extraction and Representation of Financial Entities from Text -- Quantifying News Narratives to Predict Movements in Market Risk -- Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets? -- Network Analysis for Economics and Finance: An application to Firm Ownership. 330 $aThis 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. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications. 606 $aData mining 606 $aMachine learning 606 $aManagement information systems 606 $aBig data 606 $aApplication software 606 $aInformation storage and retrieval 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 606 $aBusiness Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/522030 606 $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070 606 $aComputer Appl. in Administrative Data Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/I2301X 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 610 $aData Mining and Knowledge Discovery 610 $aMachine Learning 610 $aBusiness Information Systems 610 $aBig Data/Analytics 610 $aComputer Appl. in Administrative Data Processing 610 $aInformation Storage and Retrieval 610 $aIT in Business 610 $aComputer and Information Systems Applications 610 $aOpen Access 610 $aData Mining 610 $aBig Data 610 $aData Analytics 610 $aDecision Support Systems 610 $aSemantics and Reasoning 610 $aExpert systems / knowledge-based systems 610 $aBusiness mathematics & systems 610 $aPublic administration 610 $aInformation technology: general issues 610 $aInformation retrieval 610 $aData warehousing 615 0$aData mining. 615 0$aMachine learning. 615 0$aManagement information systems. 615 0$aBig data. 615 0$aApplication software. 615 0$aInformation storage and retrieval. 615 14$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aBusiness Information Systems. 615 24$aBig Data/Analytics. 615 24$aComputer Appl. in Administrative Data Processing. 615 24$aInformation Storage and Retrieval. 676 $a006.312 700 $aConsoli$b Sergio$4edt$01354833 702 $aConsoli$b Sergio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aReforgiato Recupero$b Diego$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSaisana$b Michaela$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484567403321 996 $aData Science for Economics and Finance$93358413 997 $aUNINA