This 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.
