Handbook of Computational Social Science for Policy

This open-access handbook provides an introduction to Computational Social Science (CSS) and its applications for policy support. It explores how to analyze and model data using CSS techniques such as big data, machine learning, and statistical learning, and discusses their potential to provide insights and information for policymaking. The handbook is structured into three parts: foundational issues, methodological aspects, and applications in various social science areas. It is intended for a wide audience, including scientists, policymakers, and private companies interested in using data to study social sciences and achieve policy impact.

Format: Hardback
Length: 490 pages
Publication date: 25 January 2023
Publisher: Springer International Publishing AG

This comprehensive handbook provides a comprehensive guide to analyzing and modeling data using Computational Social Science (CSS) for policy support. Despite the potential of CSS to significantly impact the policy cycle and enhance our understanding of societal problems, studies in this field have primarily been conducted on a small scale, limiting its ability to deliver systematic outcomes and improve policy understanding.

The primary objective of this handbook is to bridge this gap by exploring innovative approaches to data analysis and modeling for policy support. It advocates for the adoption of CSS solutions in policymaking by raising awareness of existing implementations in policy-relevant fields.

The book is organized into three parts:

Part 1: Foundations explores key policymaking areas where CSS can provide valuable insights and information, including public policy, governance, data justice, and other ethical considerations.

Part 2: Methodological Aspects delves into various computational methods and approaches, such as big data, machine learning, statistical learning, sentiment analysis, text mining, systems modeling, and network analysis. It addresses challenges related to modeling complexity, natural language processing, data validity, and innovation in official statistics.

Part 3: Applications showcases the application of computational methods in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management. It highlights challenges and opportunities associated with CSS in these domains.

The target audience of this handbook encompasses scholars, researchers, policymakers, and practitioners interested in leveraging computational methods to address complex social problems and inform policy decisions. It serves as a valuable resource for those seeking to expand their knowledge and expertise in CSS and its applications to policy.

By providing a comprehensive and accessible guide to CSS, this handbook contributes to the ongoing development of this field and its potential to drive positive social change.

Weight: 928g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031166235
Edition number: 1st ed. 2023