Computational social science

Computational social science refers to the academic sub-disciplines concerned with computational approaches to the social sciences . This means that computers are used to model, simulate, and analyze social phenomena. Fields include computational economics , computational sociology , cliodynamics , culturomics , and the automated analysis of contents, in social and traditional media. It focuses on social and behavioral interactions and interactions through social simulation , modeling, network analysis, and media analysis. [1]


There 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 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 values ​​of the scientific method : empirical research , especially through big data , by analyzing the digital footprint ; and scientific theory , especially through computer simulation model building through social simulation . [2] [3] It is a multi-disciplinary and integrated approach to social science. The computational tasks include the analysis of social networks, social geographic systems, [4] social media content and traditional media content.

Computational social science work in the field of large databases, including:

  • The Seshat: Global History Databank , which systematically collects state-of-the-art accounts of the political and social organization of human groups and societies by evolved through time into an authoritative databank . [5]Seshat is affiliated with the Evolution Institute , a non-profit think-tank that “uses evolutionary science to solve real-world problems.”
  • D-PLACE : the Database of Places, Languages, Culture and Environment, which provides data over 1,400 human social formations [6]
  • The Atlas of Cultural Evolution , an archaeological database created by Peter N. Peregrine [7]
  • CHIA: The Collaborative Information for Historical Analysis , a multidisciplinary collaborative endeavor hosted by the University of Pittsburgh with the goal of archiving historical information and linking data as academic research institutions around the globe
  • International Institute of Social History , which collects data on the global social history of labor relations, workers, and labor
  • Human Relations Area Files eHRAF ​​Archeology [8]
  • Human Relations Area Files eHRAF ​​World Cultures [9]
  • Clio-Infra a database of measures of economic performance and other aspects of societal well-being on a global sample of societies from 1800 CE to the present
  • The Google Ngram Viewer , an online search engine that charts frequencies of sets of comma-delimited search strings using a yearly count of n-grams as found in the largest online body of human knowledge, the Google Books corpus.

The analysis of large quantities of historical newspaper has been published in the past, [10] while other studies on similar data [11] . A similar analysis was performed on social media, again revealing strongly periodic structures. [12]

See also

  • Cliodynamics
  • Seshat (project)
  • Computational cognition
  • Digital sociology
  • Social web
    • Social network analysis
  • Online content analysis
  • Predictive analytics


  1. Jump up^ “The Computational Social Science Society of the Americas official website” .
  2. Jump up^ DT & SC 7-1. Introduction to e-Science: From the DT & SCOnline Courseat the University of California
  3. Jump up^ Hilbert, M. (2015). “e-Science for Digital Development: ICT4ICT4D”(PDF) . Center for Development Informatics, SEED, University of Manchester. ISBN  978-1-905469-54-3 . Archived from the original (PDF)on 2015-09-24.
  4. Jump up^ Cioffi-Revilla, Claudio (2010). “Computational social science”. Wiley Interdisciplinary Reviews: Computational Statistics . 2 (3): 259-271. doi :10.1002 / wics.95 .
  5. Jump up^ Turchin, Peter; Brennan, Rob; Currie, Thomas E .; Feeney, Kevin C .; Francois, Pieter; Hoyer, Daniel; Manning, JG; Marciniak, Arkadiusz; Mullins, Daniel; Palmisano, Alessio; Peregrine, Peter; Turner, Edward AL; Whitehouse, Harvey (2015). “Seshat: The Global History Databank”. Cliodynamics . 6 : 77.
  6. Jump up^ Kirby, Kathryn R .; Gray, Russell D .; Greenhill, Simon J .; Jordan, Fiona M .; Gomes-Ng, Stephanie; Bibiko, Hans-Jörg; Blasi, Damian E .; Botero, Carlos A .; Bowern, Claire; Ember, Carol R .; Leehr, Dan; Low, Bobbi S .; McCarter, Joe; Dival, William (2016). “D-PLACE: A Global Database of Cultural, Linguistic and Environmental Diversity”. PLoS ONE . 11 (7). doi :10.1371 / journal.pone.0158391 .
  7. Jump up^ Peter N. PeregrineAtlas of Cultural Evolution,World Cultures14 (1), 2003
  8. Jump up^ “eHRAF ​​Archeology” . Human Relations Area Files .
  9. Jump up^ “eHRAF ​​World Cultures” . Human Relations Area Files .
  10. Jump up^ Lansdall-Welfare, Thomas; Sudhahar, Saatviga; Thompson, James; Lewis, Justin; Team, FindMyPast Newspaper; Cristianini, Nello (2017-01-09). “Content analysis of 150 years of British periodicals” . Proceedings of the National Academy of Sciences : 201606380. doi : 10.1073 / pnas.1606380114 . ISSN  0027-8424 . PMID  28069962 .
  11. Jump up^ Dzogang, Fabon; Lansdall-Welfare, Thomas; Team, FindMyPast Newspaper; Cristianini, Nello (2016-11-08). “Discovering Periodic Patterns in Historical News” . PLOS ONE . 11 (11): e0165736. doi : 10.1371 / journal.pone.0165736 . ISSN  1932-6203 . PMC  5100883  . PMID  27824911 .
  12. Jump up^ Seasonal Fluctuations in Collective Mood Revealed by Searches Wikipedia and Twitter Posts Dzogang F T-Lansdall Welfare, N Cristianini – 2016 IEEE International Conference on Data Mining, Workshop onData Miningin Human Activity Analysis