词条 | Computational social science |
释义 |
DefinitionsThere are two terminologies that relate to each other: Social Science Computing (SSC) and Computational Social Science (CSS). In literature, CSS is referred to the field of social science that uses the computational approaches in studying the social phenomena. On the other hand, SSC is the field in which computational methodologies are created to assist in explanations of social phenomena. Computational social science revolutionizes both fundamental legs of the scientific method: empirical research, especially through big data, by analyzing the digital footprint left behind through social online activities; and scientific theory, especially through computer simulation model building through social simulation.[2][3] It is a multi-disciplinary and integrated approach to social survey focusing on information processing by means of advanced information technology. The computational tasks include the analysis of social networks, social geographic systems,[4] social media content and traditional media content. Computational social science work increasingly relies on the greater availability of large databases, currently constructed and maintained by a number of interdisciplinary projects, including:
The analysis of vast quantities of historical newspaper[10] and book content[11] have been pioneered in 2017, while other studies on similar data[12] showed how periodic structures can be automatically discovered in historical newspapers. A similar analysis was performed on social media, again revealing strongly periodic structures.[13] See also
References1. ^{{cite web|url=https://computationalsocialscience.org/|title=The Computational Social Science Society of the Americas official website}} 2. ^DT&SC 7-1: [https://www.youtube.com/watch?v=9x3d75ZMuYU . Introduction to e-Science]: From the DT&SC [https://canvas.instructure.com/courses/949415 online course] at the University of California 3. ^{{cite book|author=Hilbert, M.|year=2015|title=e-Science for Digital Development: ICT4ICT4D|publisher=Centre for Development Informatics, SEED, University of Manchester|url=http://www.seed.manchester.ac.uk/medialibrary/IDPM/working_papers/di/di-wp60.pdf|isbn=978-1-905469-54-3|deadurl=yes|archiveurl=https://web.archive.org/web/20150924100018/http://www.seed.manchester.ac.uk/medialibrary/IDPM/working_papers/di/di-wp60.pdf|archivedate=2015-09-24|df=}} 4. ^{{cite journal|title=Computational social science |first=Claudio |last=Cioffi-Revilla |journal=Computational Statistics |year=2010 |volume=2 |issue=3 |pages=259–271 |doi=10.1002/wics.95}} 5. ^{{cite journal|last1=Turchin|first1=Peter|last2=Brennan|first2=Rob|last3=Currie|first3=Thomas E.|last4=Feeney|first4=Kevin C.|last5=Francois|first5=Pieter|last6=Hoyer|first6=Daniel|last7=Manning|first7=J. G.|last8=Marciniak|first8=Arkadiusz|last9=Mullins|first9=Daniel|last10=Palmisano|first10=Alessio|last11=Peregrine|first11=Peter|last12=Turner|first12=Edward A. L.|last13=Whitehouse|first13=Harvey|title=Seshat: The Global History Databank|journal=Cliodynamics|date=2015|volume=6|page=77}} https://escholarship.org/uc/item/9qx38718 6. ^{{cite journal|last1=Kirby|first1=Kathryn R.|last2=Gray|first2=Russell D.|last3=Greenhill|first3=Simon J.|last4=Jordan|first4=Fiona M.|last5=Gomes-Ng|first5=Stephanie|last6=Bibiko|first6=Hans-Jörg|last7=Blasi|first7=Damián E.|last8=Botero|first8=Carlos A.|last9=Bowern|first9=Claire|last10=Ember|first10=Carol R.|last11=Leehr|first11=Dan|last12=Low|first12=Bobbi S.|last13=McCarter|first13=Joe|last14=Divale|first14=William|title=D-PLACE: A Global Database of Cultural, Linguistic and Environmental Diversity|journal=PLoS ONE|date=2016|volume=11|issue=7|pages=e0158391|doi=10.1371/journal.pone.0158391|pmid=27391016|pmc=4938595}} 7. ^Peter N. Peregrine, Atlas of Cultural Evolution, World Cultures 14(1), 2003 8. ^{{cite web|url=http://www.yale.edu/hraf/archaeology.htm|publisher=Human Relations Area Files| title=eHRAF Archaeology}} 9. ^{{cite web|url=http://ehrafworldcultures.yale.edu/ehrafe/|publisher=Human Relations Area Files| title=eHRAF World Cultures}} 10. ^{{Cite journal|last=Lansdall-Welfare|first=Thomas|last2=Sudhahar|first2=Saatviga|last3=Thompson|first3=James|last4=Lewis|first4=Justin|last5=Team|first5=FindMyPast Newspaper|last6=Cristianini|first6=Nello|date=2017-01-09|title=Content analysis of 150 years of British periodicals|url=http://www.pnas.org/content/early/2017/01/03/1606380114|journal=Proceedings of the National Academy of Sciences|volume=114|issue=4|language=en|pages=E457–E465|doi=10.1073/pnas.1606380114|issn=0027-8424|pmid=28069962|pmc=5278459}} 11. ^{{Cite journal|last=Roth|first=Steffen|display-authors=et al|date=2017|title=Futures of a distributed memory. A global brain wave measurement (1800-2000)|journal=Technological Forecasting and Social Change|volume=118|language=en|pages=307–323|doi=10.1016/j.techfore.2017.02.031}} 12. ^{{Cite journal|last=Dzogang|first=Fabon|last2=Lansdall-Welfare|first2=Thomas|last3=Team|first3=FindMyPast Newspaper|last4=Cristianini|first4=Nello|date=2016-11-08|title=Discovering Periodic Patterns in Historical News|journal=PLOS ONE|volume=11|issue=11|pages=e0165736|doi=10.1371/journal.pone.0165736|issn=1932-6203|pmc=5100883|pmid=27824911}} 13. ^Seasonal Fluctuations in Collective Mood Revealed by Wikipedia Searches and Twitter Posts F Dzogang, T Lansdall-Welfare, N Cristianini - 2016 IEEE International Conference on Data Mining, Workshop on Data Mining in Human Activity Analysis External links
4 : Social sciences|Computational science|Computational fields of study|Computational social science |
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