CURRENT RESEARCH:

BORROWING ALGORITHMIC EPISTEMOLOGIES: INVESTIGATING SOCIAL KNOWLEDGE PRODUCTION IN ALGORITHMIC MEDIATED ENVIRONMENTS

In the context of a platformized society, knowledge production is increasingly shaped by systems operating on logics distinct from traditional anthropocentric epistemologies. These systems prioritize patterns of behavior, interaction, and relationships over semantic or narrative interpretation. Rather than analyzing meaning in human terms, they construct knowledge by modeling how users act, connect, and interact with content, as well as with the grammars and affordances of platforms. Algorithms and platforms emphasize connections and regularities that often escape conscious recognition, shifting the foundation of knowledge production from a logic of signification to a logic of action.

This research is motivated by the core question: How do algorithmic epistemologies embedded in digital platforms organize knowledge about the social, and how can their logics be critically adapted to study the ways these systems know and co-produce social phenomena?

The project operates on two main fronts:

1. Understanding Algorithmic Modes of Knowing
   Algorithmic systems, such as collaborative filtering and deep learning models, categorize behaviors and interactions, determining what becomes visible and how phenomena are represented. These systems often prioritize relational and behavioral patterns over interpretive narratives, fundamentally reshaping how information is organized and accessed. This research front focuses on investigating how platforms and algorithms generate and structure knowledge, emphasizing practices and patterns of interaction rather than content itself.

2. Critically Reappropriating Algorithmic Logics
   This front proposes adapting the epistemological frameworks of these systems as analytical tools. By leveraging the logics underlying algorithmic systems, the research examines the phenomena they produce and the frameworks they use to shape knowledge. Rather than replicating proprietary algorithms, this approach reconfigures their methods to critically explore how they mediate and organize knowledge.

The project integrates media studies, science and technology studies (STS), and digital methods to examine how algorithmic systems influence cultural practices and reconfigure social structures. By using the logics of these systems as a lens, the research reflects on the dynamics of knowledge production and the broader implications of these technologies in contemporary society.