000			03277namaa2200481uu 4500
001			oapen51410
003			oapen
005			20240507100208.0
006			m o d
007			cr|mn|---annan
008			211111s2021 xx |||||o ||| 0|eng d
020			_a9780367456528
020			_a9780367456535
020			_a9781003024583
040			_aoapen _coapen
041	0		_aeng
042			_adc
072		7	_aJM _2bicssc
072		7	_aJMB _2bicssc
100	1		_aEngel, Uwe _4edt
245	1	0	_aHandbook of Computational Social Science, Vol 1 _bTheory, Case Studies and Ethics
260			_bTaylor & Francis _c2021
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
506	0		_aFree-to-read _fUnrestricted online access _2star
520			_a"The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors."
540			_aAll rights reserved _uhttp://oapen.org/content/about-rights
546			_aEnglish
650		7	_aPsychological methodology _2bicssc
650		7	_aPsychology _2bicssc
653			_aAI, big data, data analysis, data archives, data ownership, data science, digital trace, ethical standards, ethics, human-robot interaction, information technology, machine learning, open data, politics, policy, quantitative, replication, social, social media, socio-robots, survey data, survey design, survey methodology, unstructured data
700	1		_aEngel, Uwe _4oth
700	1		_aLyberg, Lars _4edt
700	1		_aLyberg, Lars _4oth
700	1		_aQuan-Haase, Anabel _4edt
700	1		_aQuan-Haase, Anabel _4oth
700	1		_aXun Liu, Sunny _4edt
700	1		_aXun Liu, Sunny _4oth
793	0		_aOAPEN Library.
856	4	0	_uhttps://library.oapen.org/handle/20.500.12657/51410 _70 _zFree-to-read: OAPEN Library: description of the publication
999			_c36512 _d36512