The Algofeed project. A methodological proposal to assessing the effects of algorithmic recommendations on platformized consumption

Abstract

[EN] This paper outlines the construction phase of the consumption profiling, algorithmic awareness, and digital literacy tool within the ALGOFEED project. ALGOFEED, funded as an Italian Research Project of Significant National Interest (PRIN), seeks to illuminate the socio-cultural impacts of platform-based feedback loops while developing a novel methodological and theoretical framework for the sociological examination of consumer culture algorithms. The project aims to produce unique empirical insights into cultural consumption patterns on digital platforms in Italy. Specifically, ALGOFEED investigates the effects of automated content recommendations on platforms like TikTok and YouTube on individual and collective cultural consumption behaviours over time. The primary objectives include acquiring distinctive empirical findings on platform-driven cultural consumption in Italy, advancing a fresh methodological and theoretical approach for studying algorithmic consumer culture sociologically, and fostering algorithmic awareness among Italian consumers through impactful diffusion activities grounded in a transformative paradigm. In this study, the authors introduce the empirical tool designed to detect the feedback loop and define its components: digital skills, Platform Usage Type, and Algorithmic Awareness.