#COTTAGECORE, #FUTURECORE, #SADCORE: USING CRITICAL SIMULATION TO EXPLORE THE INTERPLAY BETWEEN MACHINE VISION AND VERNACULAR INSTAGRAM AESTHETICS

Abstract

This paper uses a novel combination of computational and qualitative methods called ‘critical simulation’ to explore the interplay between everyday image-making practices and the algorithmic architecture of Instagram. The paper aims to understand the capacity of machine vision systems to recognise and reproduce the diverse vernacular aesthetics and affects associated with particular scenes on Instagram - in this case, drawing on a case study of Instagram’s ‘-cores’ hashtags. We used our purpose-built machine vision system to undertake unsupervised clusterings of a sample of the 359,150 images associated with a curated set of 60 ‘-cores’ hashtags, which we collected following a period of immersive qualitative investigation of the -cores phenomenon on the platform itself during 2021. We assess the extent to which the system's clusters align with the different -cores hashtags under which the images were originally posted, and then undertake a close cultural analysis of the clusters, reading them through the lens of our existing knowledge of the -core hashtags. This enables us to speculate on how the platforms’ machine vision logics might play a role in shaping Instagram’s platform aesthetics, and on internet culture more broadly.