Algorithmic consumer culture

Abstract

This article conceptualizes algorithmic consumer culture, and offers a framework that sheds new light on two previously conflicting theorizations: that (1) digitalization tends to liquefy consumer culture and thus acts primarily as an empowering force, and that (2) digitalized marketing and big data surveillance practices tend to deprive consumers of all autonomy. By drawing on critical social theories of algorithms and AI, we define and historicize the now ubiquitous algorithmic mediation of consumption, and then illustrate how the opacity, authority, non-neutrality, and recursivity of automated systems affect consumer culture at the individual, collective, and market level. We propose conceptualizing 'algorithmic articulation' as a dialectical techno-social process that allows us to enhance our understanding of platformbased marketer control and consumer resistance. Key implications and future avenues for exploring algorithmic consumer culture are discussed.

Sticky market webs of connection – human and nonhuman market co-codification dynamics across social media

“…Users appropriate and internalize this suggested sustainable fashion codex through iterative content consumption within closed, cyclical market loops. Consequently, (non)human market co-codification results in an algorithmic market culture (Airoldi and Rokka, 2019) of homogenous, territorialized codes, semantic concepts, themes, types of content and consumption practices – a sticky market web of shared market language and expressive networked content, weaving rhizomatous threads (Deleuze and Guattari, 1980) across the trenches of platformized social media. For example, the light blue cluster in Figure 7 and the purple cluster (nr.…”

“…In doing so, human market actors, moving on algorithmic territory (Rieder et al , 2018), need to stick to the vernacular of the lexical market codex to maximize content visibility. Users, in turn, find themselves, though mostly unconsciously, in “recursive relationships” (Airoldi and Rokka, 2019, p. 3) with nonhuman actors, relying on algorithm-suggested “watch next” videos. Eventually, these market dynamics result in an algorithmic market culture – closed, cyclical market loops in which human market actors’ output becomes the input for nonhuman market formation (Hallinan and Striphas, 2016).…”

“…For example, by using specific hashtag vernacular, content creators not only join affordance-mediated conversations but also redesign their expressive networked content to be better recognized and distributed by algorithms. These entangled (non)human activities eventually result in “a recursive loop between the calculations of the algorithm and the “calculations” of people” (Gillespie, 2014, p. 183), forming bubbles and algorithmic consumer cultures (Airoldi and Rokka, 2019; Carah and Brodmerkel, 2020) produced by iterative cycles of user and machine actions and corresponding responses. Algorithmic cultures manifest in vast clouds of expressive and networked cultural codes that echo with people, digital technology and infrastructure on a market level.…”

“…However, market agency cannot only be attributed to human market actors but also to digital technology such as machine learning algorithms. Agentic nonhuman entities, for example, co-create consumer experiences (Hoffman and Novak, 2018), shape algorithmic consumer culture (Airoldi and Rokka, 2019) or co-reproduce musical classification (Airoldi, 2021). Similarly, nonhuman entities are co-codifiers of market language, terminology and content; that is, market codification increasingly derives from interactional and interdependent dynamics between (non)human market actors.…”

Co-creation as choreography

“…Thus, it also taps into processual onto-epistemologies in which moving bodies navigate the spaces of value co-creation with/in materialities and other human and non-human agents. This means that value is created not only in social contexts, including humans, but also in spatio-temporal, contexts including other agents, such as animals or technological agents (Markuksela and Valtonen, 2019; Airoldi and Rokka, 2022). This also means that in these contexts, even though we learn to navigate them, we cannot be assured that we are fully in control of the meanings, experiences, and actions taking place (Haanpää et al , 2022; Parviainen and Coeckelbergh, 2021, p. 719).…”