Platformized Consumption: Algorithmic Mediation, Experience, and Cultural Practices

CALL FOR PAPERS:
Platformized Consumption: Algorithmic Mediation, Experience, and Cultural Practices

• Guest Editors: Dr. Marcelo Curth (Universidade Feevale), Dr. Sandra Portella Montardo (Universidade Feevale), Dr. Vanessa Amalia Dalpizol Valiati (Universidade Feevale), and Dr. Ítalo José de Medeiros Dantas (Universidade do Estado de Minas Gerais)
• Editor-in-Chief: Dr. Claudia Schemes

          Digital platforms occupy a central place in the organization of contemporary social life, cutting across practices of communication, entertainment, work, cultural circulation, sociability, and consumption. Rather than simply venues for offering products and services, platforms constitute sociotechnical infrastructures that articulate data, algorithms, business models, recommendation systems, interfaces, and user practices. In this context, everyday processes of choice, discovery, interaction, and consumption come to be mediated by digital architectures that not only respond to individual preferences but also actively participate in shaping and transforming them. Understanding this mediation requires attention to the ways users appropriate these architectures and integrate them into their routines, a process of domestication that spans from the acquisition to the everyday use of technologies (Von Pape; Quandt, 2010).
          Platformization can, in this sense, be understood as a process that goes beyond the mere digitization of activities previously carried out through other media. Platforms introduce specific forms of organizing interactions, content circulation, data collection and processing, monetization, and governance, through the penetration of platforms' infrastructures, economic models, and governance frameworks into different spheres of economic and cultural life (Van Dijck; Poell; De Waal, 2018; Poell; Nieborg; Duffy, 2022), including through the modular expansion of APIs, plugins, and sharing buttons that render external data "platform-ready" (Helmond, 2015). The literature on the platformization of cultural production, in turn, shows how these infrastructures interfere with the processes of production, distribution, and circulation of cultural goods (Nieborg; Poell, 2018). In the Brazilian context, Platform Studies has been consolidating itself as a perspective for investigating these phenomena through interdisciplinary appropriations (D'Andréa, 2020; Montardo, 2022).
          In the field of consumption, these transformations become particularly significant. Recommendation systems, personalization mechanisms, reviews, popularity metrics, targeted advertising, influencers, interfaces, and different forms of interaction come to integrate the processes through which consumers discover, evaluate, choose, acquire, and attribute meaning to products, services, and experiences. The act of consuming, therefore, is not limited to the moment of purchase but involves sociotechnical practices shaped by data, algorithms, and relations between users, companies, and platforms, what Airoldi and Rokka (2022) synthesize in the notion of algorithmic consumer culture, in which consumers' digital traces feed systems that come to co-produce their contexts of choice. Approaches grounded in Practice Theory offer a complementary reading, foregrounding the material aspects, competences, and meanings that sustain these consumption practices on streaming platforms (Montardo; Valiati, 2021; Valiati, 2020).
          Against this backdrop, understanding the factors that influence user behavior becomes fundamental for analyzing the new configurations of consumption. Environmental and individual elements, information quality, system quality, and service quality, trust, perceived value, convenience, personalization, social interaction, and behavioral intention all jointly shape consumption experiences in platformized environments. At the same time, data collection and processing enable platforms to identify patterns, segment audiences, and produce recommendation and prediction mechanisms that interfere with users' possibilities for choice.
          Streaming platforms, social media, marketplaces, and other digital environments do not merely make content and products available: they participate in organizing the visibility, discovery, and circulation of symbolic goods. In the case of music, for instance, recommendation systems and personalization mechanisms may interfere with modes of musical discovery, taste formation, the constitution of communities, and the relations between artists, audiences, and platforms. On streaming platforms, these processes operate through the algorithmic individuation of listeners, who are constructed as calculable audiences based on their listening data (Prey, 2018), reconfiguring the digital music commodity itself (Morris, 2015). Exploratory studies on listening on video platforms further show how recommendation networks organize navigation paths and associations between genres and artists (Airoldi; Beraldo; Gandini, 2016). In the Brazilian case, the appropriation of features such as Spotify Wrapped illustrates how users publicly perform algorithmic taste identities, turning listening data into narratives of self-making shared across social media (Valiati; Lupinacci; Soares, 2026). The consumption experience thus involves feedback loops in which users' practices feed the algorithmic systems that, in turn, reorganize what will be presented to them.
          This dynamic allows us to think of the algorithm not merely as a technical resource but as a mediating element of cultural and consumption experiences. By selecting, ordering, recommending, classifying, and rendering certain content more visible than other content, algorithmic systems participate in constructing the possibilities for choice and discovery. For Gillespie (2014), relevance algorithms operate as knowledge logics that define what counts as pertinent information for each user; Bucher (2018) shows that these operations are also productive, organizing regimes of visibility and anticipation. In the domain of taste, Seaver (2022) shows that music recommendation systems result from the situated practices of developers seeking to capture and formalize preferences, while Airoldi (2022) proposes the notion of machine habitus to think about the reciprocal socialization between users and machines in the formation of consumption dispositions. The question is therefore not only what individuals consume, but how particular infrastructures, recommendation logics, and forms of mediation produce specific conditions for particular forms of consumption to occur.
          It is within this context that this special issue invites research investigating the relations between algorithms, digital platforms, consumption practices, and cultural processes, addressing both the factors that influence user behavior and the processes through which platforms participate in the production of tastes, experiences, identities, values, and forms of cultural participation. The call is interdisciplinary in scope, welcoming contributions from Communication, Business Administration, Marketing, Sociology, Anthropology, Design, Fashion, Cultural Studies, Music, the Arts, Information Science, and related fields.
          Quantitative, qualitative, and mixed-methods research, digital methods, algorithm audits, reception studies, interviews, focus groups, digital ethnographies, platform analysis, and other methodological strategies relevant to the phenomena under investigation are welcome.
          Suggested topics, among others, include:
          • Platformization of specific cultural and creative sectors (music, audiovisual, fashion, games, among others);
          • Recommendation systems, algorithmic curation, and cultural discovery;
          • Datafication, personalization, and privacy in consumption;
          • Appropriation of platforms and technologies by users;
          • Performance of identity and taste in algorithmic environments;
          • Digital methods and methodological approaches for studying algorithms and platforms.
          This list is not exhaustive, and contributions that engage with the special issue's broader scope are welcome.

Submission Guidelines:
          • Original articles in English, Portuguese, or Spanish are welcome.
          • Submissions must follow the journal's submission guidelines.
          • All articles will undergo double-blind peer review.

• Submission deadline: May 31, 2027.
• Expected publication: By August 31, 2027 (second issue of 2027).

References
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