Molinari B. From digital traces to artificial intelligence: New boundaries from representativeness

Authors: Beba Molinari

Abstract

The abstract aims to highlight what contribution Artificial Intelligence can make in the field of social research by setting as a fixed point the tools to date established in research methodology, whether traditional or closely related to e-methods. It is necessary to stop and think about how and what data AI provides us with by asking: are we in the same scope of analysis as e-methods? Instead, can we continue to handle such data through traditional analysis techniques, or should we think of AI as totally new data/information? These are just a few questions that will be attempted to be answered without any claim to exhaustiveness of course, but aimed at discussing representativeness and margin of error not only statistically, but understood in a much broader sense.

Keywords: Artificial Intelligence, Big Data, E-methods, Machine learning

DOI: https://doi.org/10.13131/unipi/x6c5-2t23

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Notes on contributors

BEBA MOLINARI  is a researcher of Sociology at the University of Rome Tor Vergata.
Email: beba.molinari@uniroma2.it

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