首页|How Do Social Media Algorithms Appear? A Phenomenological Response to the Black Box Metaphor

How Do Social Media Algorithms Appear? A Phenomenological Response to the Black Box Metaphor

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This article challenges the dominant ‘black box’ metaphor in critical algorithm studies by proposing a phenomenological framework for understanding how so-cial media algorithms manifest themselves in user experience. While the black box paradigm treats algorithms as opaque, self-contained entities that exist only ‘behind the scenes’, this article argues that algorithms are better understood as genetic phe-nomena that unfold temporally through user-platform interactions. Recent schol-arship in critical algorithm studies has already identified various ways in which algorithms manifest in user experience: through affective responses, algorithmic self-reflexivity, disruptions of normal experience, points of contention, and folk theories. Yet, while these studies gesture toward a phenomenological understanding of algorithms, they do so without explicitly drawing on phenomenological theory. This article demonstrates how phenomenology, particularly a Husserlian genetic approach, can further conceptualize these already-documented algorithmic encoun-ters. Moving beyond both the paradigm of artifacts and static phenomenological approaches, the analysis shows how algorithms emerge as inherently relational processes that co-constitute user experience over time. By reconceptualizing algo-rithms as genetic phenomena rather than black boxes, this paper provides a theo-retical framework for understanding how algorithmic awareness develops from pre-reflective affective encounters to explicit folk theories, while remaining inextricably linked to users’ self-understanding. This phenomenological framework contributes to a more nuanced understanding of algorithmic mediation in contemporary social media environments and opens new pathways for investigating digital technologies.

AlgorithmsBlack boxSocial mediaPhenomenologyGenetic phenomena

Anthony Longo

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Department of Philosophy, University of Antwerp, Rodestraat 14, Antwerp 2000, Belgium

2025

Minds and machines

Minds and machines

ISSN:0924-6495
年,卷(期):2025.35(2)