| 書目名稱 | Data Science for Social Good | | 副標題 | Philanthropy and Soc | | 編輯 | Massimo Lapucci,Ciro Cattuto | | 視頻video | http://file.papertrans.cn/264/263122/263122.mp4 | | 概述 | Provides timely research on data science for social impact, with connections to complex systems, machine learning and artificial intelligence.Offers contributed chapters by recognized, world-class lea | | 叢書名稱 | SpringerBriefs in Complexity | | 圖書封面 |  | | 描述 | This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact – identifying a social need, targeting an intervention, measuring impact – and the complementary perspective of funders and philanthropies that are pushing forward this new sector.?.This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.. | | 出版日期 | Book 2021 | | 關鍵詞 | Philanthropy in Science; Digital Demography; Data Collaboratives; Digital Epidemiology; Data for Good; Ar | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-78985-5 | | isbn_softcover | 978-3-030-78984-8 | | isbn_ebook | 978-3-030-78985-5Series ISSN 2191-5326 Series E-ISSN 2191-5334 | | issn_series | 2191-5326 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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