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It’s time to scale the science in the social sciences:

It’s time to scale the science in the social sciences: The social sciences are at a remarkable confluence of events. Advances in computing have made it feasible to analyze data at the scale of the population of the world. How can we combine the depth of inquiry in the social sciences with the scale and robustness of statistics and computer science? Can we decompose complex questions in the social sciences into simpler, more robustly testable hypotheses? We discuss these questions and the role of machine learning in the social sciences. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Big Data & Society SAGE

It’s time to scale the science in the social sciences:

Big Data & Society , Volume 1 (1): 1 – Apr 1, 2014

It’s time to scale the science in the social sciences:

Big Data & Society , Volume 1 (1): 1 – Apr 1, 2014

Abstract

The social sciences are at a remarkable confluence of events. Advances in computing have made it feasible to analyze data at the scale of the population of the world. How can we combine the depth of inquiry in the social sciences with the scale and robustness of statistics and computer science? Can we decompose complex questions in the social sciences into simpler, more robustly testable hypotheses? We discuss these questions and the role of machine learning in the social sciences.

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Publisher
SAGE
Copyright
Copyright © 2022 by SAGE Publications Ltd, unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses.
ISSN
2053-9517
eISSN
2053-9517
DOI
10.1177/2053951714532240
Publisher site
See Article on Publisher Site

Abstract

The social sciences are at a remarkable confluence of events. Advances in computing have made it feasible to analyze data at the scale of the population of the world. How can we combine the depth of inquiry in the social sciences with the scale and robustness of statistics and computer science? Can we decompose complex questions in the social sciences into simpler, more robustly testable hypotheses? We discuss these questions and the role of machine learning in the social sciences.

Journal

Big Data & SocietySAGE

Published: Apr 1, 2014

Keywords: Data analysis; machine learning; social sciences; robust methodology; computational aesthetics; scalable science

References