001452696 000__ 03810cam\a22004937i\4500
001452696 001__ 1452696
001452696 003__ OCoLC
001452696 005__ 20230314003314.0
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001452696 007__ cr\cn\nnnunnun
001452696 008__ 230201s2023\\\\sz\a\\\\ob\\\\000\0\eng\d
001452696 020__ $$a9783031166242$$q(electronic bk.)
001452696 020__ $$a3031166248$$q(electronic bk.)
001452696 020__ $$z9783031166235
001452696 0247_ $$a10.1007/978-3-031-16624-2$$2doi
001452696 035__ $$aSP(OCoLC)1368010371
001452696 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP
001452696 049__ $$aISEA
001452696 050_4 $$aH61.3
001452696 08204 $$a300.72/7$$223/eng/20230201
001452696 24500 $$aHandbook of computational social science for policy /$$cEleonora Bertoni, Matteo Fontana, Lorenzo Gabrielli, Serena Signorelli, Michele Vespe, editors.
001452696 264_1 $$aCham, Switzerland :$$bSpringer,$$c2023.
001452696 300__ $$a1 online resource (xxi, 490 pages) :$$billustrations.
001452696 336__ $$atext$$btxt$$2rdacontent
001452696 337__ $$acomputer$$bc$$2rdamedia
001452696 338__ $$aonline resource$$bcr$$2rdacarrier
001452696 504__ $$aIncludes bibliographical references (page 490).
001452696 5060_ $$aOpen access$$5GW5XE
001452696 520__ $$aThis 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.
001452696 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 1, 2023).
001452696 650_0 $$aSocial sciences$$xData processing.
001452696 650_0 $$aSocial sciences$$xMethodology.
001452696 655_0 $$aElectronic books.
001452696 7001_ $$aBertoni, Eleonora,$$eeditor.
001452696 7001_ $$aFontana, Matteo,$$eeditor.
001452696 7001_ $$aGabrielli, Lorenzo,$$eeditor.
001452696 7001_ $$aSignorelli, Serena,$$eeditor.
001452696 7001_ $$aVespe, Michele,$$eeditor.
001452696 852__ $$bebk
001452696 85640 $$3Springer Nature$$uhttps://link.springer.com/10.1007/978-3-031-16624-2$$zOnline Access$$91397441.2
001452696 909CO $$ooai:library.usi.edu:1452696$$pGLOBAL_SET
001452696 980__ $$aBIB
001452696 980__ $$aEBOOK
001452696 982__ $$aEbook
001452696 983__ $$aOnline
001452696 994__ $$a92$$bISE