Machine learning, artificial neural networks and social research

Giovanni Di Franco () and Michele Santurro ()
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Giovanni Di Franco: Sapienza University of Rome
Michele Santurro: Sapienza University of Rome

Quality & Quantity: International Journal of Methodology, 2021, vol. 55, issue 3, No 11, 1007-1025

Abstract: Abstract Machine learning (ML), and particularly algorithms based on artificial neural networks (ANNs), constitute a field of research lying at the intersection of different disciplines such as mathematics, statistics, computer science and neuroscience. This approach is characterized by the use of algorithms to extract knowledge from large and heterogeneous data sets. In addition to offering a brief introduction to ANN algorithms-based ML, in this paper we will focus our attention on its possible applications in the social sciences and, in particular, on its potential in the data analysis procedures. In this regard, we will provide three examples of applications on sociological data to assess the impact of ML in the study of relationships between variables. Finally, we will compare the potential of ML with traditional data analysis models.

Keywords: Machine learning; Deep learning Artificial neural network; Supervised learning; Linear models; Nonlinear models (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11135-020-01037-y

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