This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing implementations of CSS in policy-relevant fields.

To this end, the book explores applications of computational methods and approaches like big data, machine learning, statistical learning, sentiment analysis, text mining, systems modelling, and network analysis to different problems in the social sciences. The book is structured into three Parts: the first chapters on foundational issues open with an exposition and description of key policymaking areas where CSS can provide insights and information. In detail, the chapters cover public policy, governance, data justice and other ethical issues. Part two consists of chapters on methodological aspects dealing with issues such as the modelling of complexity, natural language processing, validity and lack of data, and innovation in official statistics. Finally, Part three describes the application of computational methods, challenges and opportunities in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management.

The target audience of the book spans from the scientific community engaged in CSS research to policymakers interested in evidence-informed policy interventions, but also includes private companies holding data that can be used to study social sciences and are interested in achieving a policy impact.

�ber die Autorin bzw. den Autor

Eleonora Bertoni is a Project Officer – Computational Social Scientist at the European Commission, Joint Research Centre (JRC), where she works for the Centre of Advanced Studies (CAS). She coordinates the activities of the CAS group on Computational Social Science for Policy which aims at building capacity in accessing and analysing non-traditional data, as well as exploring applications of computational methods in different social sciences domains to address specific policy questions.
Matteo Fontana is a Project Officer - Data Scientist at the Joint Research Centre of the European Commission. His main research interest is the application and development of data science and statistical learning techniques to evaluate complex data sources in the social sciences field. He is particularly interested in nonparametric inference and prediction, with a focus on conformal methods for complex data. From an applicative point of view, he is interested in macro-economic forecasting, migration modelling and environmental economics.
Lorenzo Gabrielli is a Data Scientist in the JRC Centre for Advanced Studies (CAS) Project on Computational Social Science for Policy to carry out scientific tasks, i.e. harness non-traditional data including big data, analyse it and draw conclusions on its impact on society. He has gained experience in the analysis of big data with data mining and machine learning techniques in national and international contexts by collaborating with several public and private research institutes.
Serena Signorelli works as a Data Partnership and Management Officer at the Joint Research Centre. Her current project focuses on Computational Social Science for Policy, and it is part of the Centre for Advanced Studies of the Scientific Development unit. Her research interests have mainly focused on the use of Wikipedia page views to study tourism flows, and they havebeen exploited through a traineeship and a subsequent contract with the Eurostat Big Data task force.
Michele Vespe is a Team Leader at the European Commission, Joint Research Centre, where he coordinates the activities of teams of researchers for investigating societal consequences associated with the improved availability of digital trace data, including research in the fields of data governance. He also leads the Computational Social Science for Policy project team.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

Anbieterinformationen

We sell Brand New University Textbooks to students at very affordable prices. All orders are shipped by Trackable methods only and the tracking number is available within 48 hours of placing the order. We also offer free shipping to USA, Canada and Europe and lowest shipping charges in other countries. We have multiple warehouses to save on the transit time.

Zur Homepage des Verk�ufers

Unternehmensdaten des Verk�ufers

SMASS Group LLC
1944 Loma Linda Dr, Irving, TX, 75063, U.S.A.

Gesch�ftsbedingungen und Versandinformationen

Verkaufsbedingungen

We sell Brand New Textbooks requied for studies in the Univesity. We have been in this business for the past 14 years and we know how to keep our customers happy and satisfies by providing them the required course material and the most affordable prices.

Widerrufsbelehrung

Versandbedingungen

We ship all orders from our Multiple warehouses by Tracakble method only. We have tie up with Fedex, DHL, UPS and USPS for our logistics requirements. All tracking numbers are available within 48 hours of processing the order.

Versandkosten innerhalb von USA

Versandkosten innerhalb von USA
Bestellmenge	5 bis 10�Werktage	3 bis 6�Werktage
Erster Artikel	EUR 0.00	EUR 0.00

Die Versandzeiten werden von den Verk�uferinnen und Verk�ufern festgelegt. Sie variieren je nach Versanddienstleister und Standort. Sendungen, die den Zoll passieren, k�nnen Verz�gerungen unterliegen. Eventuell anfallende Abgaben oder Geb�hren sind von der K�uferin bzw. dem K�ufer zu tragen. Die Verk�uferin bzw. der Verk�ufer kann Sie bez�glich zus�tzlicher Versandkosten kontaktieren, um einen m�glichen Anstieg der Versandkosten f�r Ihre Artikel auszugleichen.