Next Article in Journal
Cyberbullying Victimization and Perpetration, Connectedness, and Monitoring of Online Activities: Protection from Parental Figures
Previous Article in Journal
Refuge in the City
Previous Article in Special Issue
Big Data, Algorithmic Regulation, and the History of the Cybersyn Project in Chile, 1971–1973
Article Menu

Export Article

Open AccessArticle

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

Universidade de Lisboa, Instituto de Ciências Sociais, Av. Professor Aníbal de Bettencourt 9, 1600-189 Lisboa, Portugal
Soc. Sci. 2018, 7(12), 264; https://doi.org/10.3390/socsci7120264
Received: 31 October 2018 / Revised: 3 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
(This article belongs to the Special Issue Big Data and the Human and Social Sciences)
  |  
PDF [268 KB, uploaded 11 December 2018]

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. View Full-Text
Keywords: human and social sciences; data science; big data; distant reading; cultural analytics; statistics of culture; positivism/interpretivism/interactionism human and social sciences; data science; big data; distant reading; cultural analytics; statistics of culture; positivism/interpretivism/interactionism
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Martinho, T.D. Researching Culture through Big Data: Computational Engineering and the Human and Social Sciences. Soc. Sci. 2018, 7, 264.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Soc. Sci. EISSN 2076-0760 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top