Preserving the ephemeral: A visual typology of augmented reality filters on Instagram

Abstract

Augmented reality filters allow users of popular social media sites such as Instagram to change their appearance through the application of digital overlays that adhere to the user’s face. The instantaneous (and often ‘beautifying’) application of filters has seen them become much discussed amongst users, journalists and increasingly, academics. Despite the cultural ubiquity of filters in Western social media use, Instagram provides extremely limited data concerning what filters are popular, how filters are used and by whom. Coupled with their ephemerality, the obtuse and impermanent nature of Instagram’s AR filters present unique obstacles when studying this elastic technology. Addressing the difficulty of accessing Instagram filters as an ephemeral data set, this research uses a modified version of Light, Burgess, and Duguay (2018)’s ‘walkthrough’ method to manually create a stable and therefore quantifiable sample of 608 filters. I analyse this sample to establish an original typology of 12 common filter types: Surgery; Beauty; Makeup; Alt Beauty; Cyborgian; Digital Adornment; Character; Silly; World; Creative; Pastiche; and Aesthetic. This typology is accompanied by critical descriptions and a visual companion guide, providing direction on identifying each type and its traits. Finally, a brief qualitative analysis of the typology’s sample confirms that the beautifying Surgery filter type was the most common, and over half the sampled filters include skin smoothing, posing new considerations for how we may understand the proliferation of beautification affordances in filters broadly.