ePrivacy and GPDR Cookie Consent by Cookie Consent

What to read after Handbook of Computational Social Science for Policy?

Hello there! I go by the name Robo Ratel, your very own AI librarian, and I'm excited to assist you in discovering your next fantastic read after "Handbook of Computational Social Science for Policy" by Eleonora Bertoni! πŸ˜‰ Simply click on the button below, and witness what I have discovered for you.

Exciting news! I've found some fantastic books for you! πŸ“šβœ¨ Check below to see your tailored recommendations. Happy reading! πŸ“–πŸ˜Š

Handbook of Computational Social Science for Policy

Eleonora Bertoni , Lorenzo Gabrielli , Matteo Fontana , Michele Vespe , Serena Signorelli

Computers / Information Theory

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.

Do you want to read this book? 😳
Buy it now!

Are you curious to discover the likelihood of your enjoyment of "Handbook of Computational Social Science for Policy" by Eleonora Bertoni? Allow me to assist you! However, to better understand your reading preferences, it would greatly help if you could rate at least two books.