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BuchGebunden
490 Seiten
Englisch
Springererschienen am25.01.20231st ed. 2023
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.mehr
Verfügbare Formate
BuchGebunden
EUR53,49
Book on DemandKartoniert, Paperback
EUR42,79

Produkt

KlappentextThis 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.
Details
ISBN/GTIN978-3-031-16623-5
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2023
Erscheinungsdatum25.01.2023
Auflage1st ed. 2023
Seiten490 Seiten
SpracheEnglisch
IllustrationenXXI, 490 p. 1 illus.
Artikel-Nr.51013259

Inhalt/Kritik

Inhaltsverzeichnis
- Part I Foundational Issues. - 1. Computational Social Science for Public Policy. - 2. Computational Social Science for the Public Good: Towards a Taxonomy of Governance and Policy Challenges. - 3. Data Justice, Computational Social Science and Policy. - 4. The Ethics of Computational Social Science. - Part II Methodological Aspects. - 5.  Modelling Complexity with Unconventional Data: Foundational Issues in Computational Social Science. - 6. From Lack of Data to Data Unlocking. - 7. Natural Language Processing for Policymaking. - 8. Describing Human Behaviour Through Computational Social Science. - 9. Data and Modelling for the Territorial Impact Assessment (TIA) of Policies. - 10. Challenges and Opportunities of Computational Social Science for Official Statistics. - Part III Applications. - 11. Agriculture, Food and Nutrition Security: Concept, Datasets and Opportunities for Computational Social Science Applications. - 12. Big Data and Computational Social Science for Economic Analysis and Policy. - 13. Changing Job Skills in a Changing World. - 14. Computational Climate Change: How Data Science and Numerical Models Can Help Build Good Climate Policies and Practices. - 15. Digital Epidemiology. - 16. Learning Analytics in Education for the Twenty-First Century. - 17. Leveraging Digital and Computational Demography for Policy Insights. - 18. New Migration Data: Challenges and Opportunities. - 19. New Data and Computational Methods Opportunities to Enhance the Knowledge Base of Tourism. - 20. Computational Social Science for Policy and Quality of Democracy: Public Opinion, Hate Speech, Misinformation, and Foreign Influence Campaigns. - 21. Social Interactions, Resilience, and Access to Economic Opportunity: A Research Agenda for the Field of Computational Social Science. - 22. Social Media Contribution to the Crisis Management Processes: Towards a More Accurate Response Integrating Citizen-Generated Content and Citizen-Led Activities. - 23. The Empirical Study of Human Mobility: Potentials and Pitfalls of Using Traditional and Digital Data. - 24. Towards a More Sustainable Mobility.mehr

Schlagworte

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.
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