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

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Abstract

This article challenges the dominant ‘black box’ metaphor in critical algorithm studies by proposing a phenomenological framework for understanding how social 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 phenomena that unfold temporally through user-platform interactions. Recent scholarship 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 encounters. 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 algorithms as genetic phenomena rather than black boxes, this paper provides a theoretical 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.

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Notes

  1. It must be added here that algorithms not only change along with the event, as if events in the world (as datafied) pre-exist and the algorithm follows; rather algorithms stand in much more complex relations to reality as they can also change the course of events in itself. Bucher gives the example of how the Google Flu Tracker in 2011–2013, by recommending flu-related search terms through auto-completion, was itself ‘producing the conditions it was trying to merely describe and predict’ (Bucher, 2018, p. 28). There is an emerging literature on such instances of algorithmically mediated ‘self-fulfilling’ and ‘self-defeating’ prophecies (King & Mertens, 2023; cf. Mertens et al., 2022).

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The research conducted for this article was funded by the Research Foundation – Flanders (FWO). Grant number: 1119522 N.

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    Anthony Longo

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Longo, A. How Do Social Media Algorithms Appear? A Phenomenological Response to the Black Box Metaphor. Minds & Machines 35, 15 (2025). https://doi.org/10.1007/s11023-025-09716-1

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