Handbook of Computational Social Science for Policy
暫譯: 政策計算社會科學手冊

Bertoni, Eleonora, Fontana, Matteo, Gabrielli, Lorenzo

Handbook of Computational Social Science for Policy
  • 出版商: Springer
  • 出版日期: 2023-01-25
  • 售價: $2,390
  • 貴賓價: 9.5 折 $2,271
  • 語言: 英文
  • 頁數: 486
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 303116623X
  • ISBN-13: 9783031166235

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

這本開放存取的手冊描述了使用計算社會科學（Computational Social Science, CSS）進行政策支持的基礎問題、方法論方法及範例。迄今為止，CSS 研究大多在小規模的概念驗證階段發展，這限制了其在政策循環中提供系統性影響的潛力，也妨礙了對社會問題的理解，從政策的定義、評估、評價到監測。這本手冊的目標是填補這一空白，探索用於政策支持的數據分析和建模方法，並通過提高對現有 CSS 在政策相關領域實施的認識，倡導在政策中採用 CSS 解決方案。

為此，本書探討了計算方法和方法論的應用，如大數據、機器學習、統計學習、情感分析、文本挖掘、系統建模和網絡分析，針對社會科學中的不同問題。本書分為三個部分：第一部分的章節針對基礎問題，開篇介紹了 CSS 可以提供見解和信息的關鍵政策制定領域。具體而言，這些章節涵蓋了公共政策、治理、數據正義及其他倫理問題。第二部分包含了關於方法論方面的章節，處理如複雜性建模、自然語言處理、有效性和數據缺乏、以及官方統計創新等問題。最後，第三部分描述了計算方法在各種社會科學領域的應用、挑戰和機會，包括經濟學、社會學、人口學、移民、氣候變遷、流行病學、地理學和災害管理。

本書的目標讀者涵蓋了從參與 CSS 研究的科學社群到對基於證據的政策干預感興趣的政策制定者，還包括持有可用於研究社會科學的數據並希望實現政策影響的私營公司。

作者簡介

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 have been 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.


作者簡介(中文翻譯)

埃莉諾拉·貝爾托尼是歐洲委員會聯合研究中心（JRC）的專案官員 - 計算社會科學家，任職於高級研究中心（CAS）。她負責協調CAS小組在政策上的計算社會科學活動，旨在提升訪問和分析非傳統數據的能力，並探索計算方法在不同社會科學領域中的應用，以解決特定的政策問題。

馬泰奧·方塔納是歐洲委員會聯合研究中心的專案官員 - 數據科學家。他的主要研究興趣是應用和發展數據科學及統計學習技術，以評估社會科學領域中的複雜數據來源。他特別關注非參數推斷和預測，專注於複雜數據的符合方法。在應用層面上，他對宏觀經濟預測、移民建模和環境經濟學感興趣。

洛倫佐·加布里埃利是JRC高級研究中心（CAS）計算社會科學政策專案的數據科學家，負責執行科學任務，即利用非傳統數據（包括大數據）進行分析，並得出其對社會影響的結論。他在國內和國際背景下，通過與多個公共和私人研究機構的合作，積累了使用數據挖掘和機器學習技術分析大數據的經驗。

塞雷娜·西尼奧雷利在聯合研究中心擔任數據夥伴關係和管理官員。她目前的專案專注於政策的計算社會科學，並且是科學發展單位高級研究中心的一部分。她的研究興趣主要集中在使用維基百科頁面瀏覽量來研究旅遊流量，並通過實習和隨後與歐洲統計局大數據工作組的合同進行了相關研究。

米凱萊·維斯佩是歐洲委員會聯合研究中心的團隊領導，負責協調研究團隊的活動，以調查與數字痕跡數據可用性改善相關的社會後果，包括數據治理領域的研究。他還領導計算社會科學政策專案團隊。

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