{"product_id":"data-science-for-economics-and-finance-methodologies-and-applications-paperback","title":"Data Science for Economics and Finance: Methodologies and Applications - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eSergio Consoli\u003c\/b\u003e (Editor), \u003cb\u003eDiego Reforgiato Recupero\u003c\/b\u003e (Editor), \u003cb\u003eMichaela Saisana\u003c\/b\u003e (Editor)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e \u003cp\u003eThe 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. \u003c\/p\u003e \u003cp\u003eThis 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. \u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003cb\u003e​\u003c\/b\u003e\u003cb\u003eSergio Consoli\u003c\/b\u003e is a Scientific Project Officer at the European Commission, Joint Research Centre, Italy, working on the project \"Big Data and Forecasting of Economic Developments\" aiming at exploring novel big data sources and methodologies to provide better economic forecasting. Formerly Sergio was a Senior Scientist within the Data Science department at Philips Research, a Computer Engineering Officer at the Italian Presidency of the Council of Ministers, and a Junior Researcher at the National Research Council of Italy. Sergio's education and scientific experience fall in the areas of data science, operations research, artificial intelligence, knowledge engineering, and machine learning. He is author of several research publications in peer-reviewed international journals, granted patents, edited books, and leading conferences in these fields. \u003cb\u003e\u003cbr\u003e\u003c\/b\u003e\u003cb\u003eDiego Reforgiato Recupero\u003c\/b\u003e is an Associate Professor at the Department of Mathematics and Computer Science of the University of Cagliari, Italy, where he is also a member of the Technical Commission for Patents and Spin-offs. His interests span from Semantic Web, graph theory, and smart grid optimization to sentiment analysis, data mining, big data, natural language processing, and human-robot interaction. He is the author of several research publications in peer-reviewed international journals, edited books, and leading conferences in these fields. He is Director of the Laboratory of Human Robot Interaction and Co-Director of the Laboratory of Artificial Intelligence and Big Data. He is also affiliated with the National Research Council of Italy (CNR) where he is a member of the Semantic Technology Laboratory and passionate about bringing the research output to the market. \u003cbr\u003e\u003cb\u003eMichaela Saisana\u003c\/b\u003e is Head of the Monitoring, Indicators and Impact Evaluation Unit and she also leads the European Commission's Competence Centre on Composite Indicators and Scoreboards (COIN) at the Joint Research Centre in Italy. She has been working in the JRC since 1998, where she obtained a prize as \"Best Young Scientist of the Year\" in 2004 and together with her team the \"JRC Policy Impact Award\" for the Social Scoreboard of the European Pillar of Social Rights in 2018. Specializing on process optimization and spatial statistics, she is actively involved in promoting a sound development and responsible use of performance monitoring tools which feed into EU policy formulation and legislation in a wide range of fields. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 355\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.77 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e June 10, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52493655277875,"sku":"9783030668938","price":87.98,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/OGNDbXhEckREc2pTTVdvSHp2aFBNUT09.webp?v=1759960639","url":"https:\/\/www.vysn.com\/en-ca\/products\/data-science-for-economics-and-finance-methodologies-and-applications-paperback","provider":"VYSN","version":"1.0","type":"link"}