Abstract

ZELCER, Mariano. Machine learning and semiotic logics: the case of digital advertising. Trama comun. [online]. 2022, vol.26, n.2, pp.15-31. ISSN 1668-5628.

This article introduces an approach to the computer machine learning processes from Peirce’s semiotics perspective. To reach this aim, it works in a territory where the machine learning management of data obtained through users’ datafication becomes clearly visible: digital advertising. Based on a real case, it describes the ways in which machine learning articulates abductive and inductive logics, focusing on how computer systems generate hypotheses based on the identification of similarities and test them in experimental research, whose results work as a new input that feeds back into learning.

Keywords : Digital Advertising; Machine learning; Datafication; Semiotics; Abduction.

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