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Researching Culture through Big Data: Computational Engineering and the Human and Social Sciences

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  • Teresa Duarte Martinho

    (Universidade de Lisboa, Instituto de Ciências Sociais, Av. Professor Aníbal de Bettencourt 9, 1600-189 Lisboa, Portugal)

Abstract

The emergence of big data and data science has caused the human and social sciences to reconsider their aims, theories, and methods. New forms of inquiry into culture have arisen, reshaping quantitative methodologies, the ties between theory and empirical work. The starting point for this article is two influential approaches which have gained a strong following, using computational engineering for the study of cultural phenomena on a large scale: ‘distant reading’ and ‘cultural analytics’. The aim is to show the possibilities and limitations of these approaches in the pursuit of scientific knowledge. The article also focuses on statistics of culture, where integration of big data is challenging procedures. The article concludes that analyses of extensive corpora based on computing may offer significant clues and reveal trends in research on culture. It argues that the human and social sciences, in joining up with computational engineering, need to continue to exercise their ability to perceive societal issues, contextualize objects of study, and discuss the symbolic meanings of extensive worlds of artefacts and discourses. In this way, they may help to overcome the perceived restrictions of large-scale analysis such as the limited attention given to individual actors and the meanings of their actions.

Suggested Citation

  • Teresa Duarte Martinho, 2018. "Researching Culture through Big Data: Computational Engineering and the Human and Social Sciences," Social Sciences, MDPI, vol. 7(12), pages 1-17, December.
  • Handle: RePEc:gam:jscscx:v:7:y:2018:i:12:p:264-:d:189637
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    1. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.
    2. Mehrdad Yazdani & Jay Chow & Lev Manovich, 2017. "Quantifying the development of user-generated art during 2001–2010," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-24, August.
    3. Francesco Boldizzoni, 2011. "The Poverty of Clio: Resurrecting Economic History," Economics Books, Princeton University Press, edition 1, number 9476.
    4. Eric P. S. Baumer & David Mimno & Shion Guha & Emily Quan & Geri K. Gay, 2017. "Comparing grounded theory and topic modeling: Extreme divergence or unlikely convergence?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(6), pages 1397-1410, June.
    5. Halford, Susan & Savage, Mike, 2017. "Speaking sociologically with big data: symphonic social science and the future for big data research," LSE Research Online Documents on Economics 87236, London School of Economics and Political Science, LSE Library.
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