SCROLL, PRINT, ALGORITHMICALLY CLUSTER: A CO-ANALYSIS APPROACH TO EXPLORE THE INTERPLAY BETWEEN USERS, PLATFORMS AND ALGORITHMIC MODELS ON INSTAGRAM

Resumen

Over the past fifteen years Instagram has industrialised and platformised the everyday practices of creating and sharing digital images. Our posts and stories are both an archive of our lives and visual practices, but also part of the historical process of assembling image data sets for training machine vision systems. This paper presents the final part of a multi-year project where we use a combination of cultural and computational methods to explore the relationships between our everyday image-making practices and the algorithmic models of Instagram (Authors). We present findings from a study with 25 participants who have used Instagram for five or more years as part of their professional or creative practices. Participants downloaded and donated their complete archive of Instagram posts and stories. We then printed out 500 images from their profile as photographs and clustered their entire archive using our purpose-built machine vision system. In a co-analysis interview participants scrolled back through their Instagram profile, narrating changes in their practices and the platform over time. They then manually sorted the images printed from their archive and explored a visualisation of the algorithmic clustering of their images. Through this process of co-analysis we elicit the algorithmic imaginary of users and develop an intimate platform biography of how their practices are entangled with platform interfaces and algorithmic models.