Gender stereotypes in TikTok and Instagram: a reverse engineering experiment for understanding the mechanisms of social network algorithms
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Abstract
In the context of immersion of digital content during the Covid-19 pandemic, the popularization of algorithmic
mechanisms for curating information in everyday life was evident. This article presents the observations
of a reverse engineering experiment carried out at PUCRS (Brazil) in which evidence of the reinforcement (or
not) of gender stereotypes in social networks was sought. For this, accounts were created on the TikTok and Instagram apps, one identified with male pronouns, the other with female pronouns. The study was divided into phases in which the levels of interaction with the content of the applications were changed so that it was possible to analyze the transformations in the recommended videos to identify clues to the mechanism used by the platform. Finally, it was possible to observe differences between the content suggested for each profile that
may be related to gender stereotypes and differences in quality and popular topics in each application. It was
also possible to perceive which actions seemed to have more interference in the recommendations and which
type of content or interaction was prioritized for each network. This study does not intend to end the discussions
on how social networks operate but to bring new questions and reflections on the parameters used by their logic and the possible positive and negative effects of these recommendations in different social contexts.
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