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Citation

Bernardi C & Alhamdan N (2021) Digital Traces and Feminist Data Studies [Social media and visual traces]., 31.08.2021-03.09.2021. https://www.europeansociology.org/esa-conference-2021-in-barcelona

Abstract
This paper applies gender reflections on benevolent sexism and revisits it to interpret and analyse the Instagram hashtag network #DownSyndrome. Combining propositions of Actor Network Theories applications to mapping controversies online, disability studies and behavioural sciences, the paper discusses the networks of discussions generated online around the hashtag #Down Syndrome. A data set comprising of over 14,000 images and associated posts is analysed. Text analysis includes Social Network Analysis, topic modelling and time series analysis. Computer vision and time series analysis are undertaken for images. The objective is to identify rhetoric that emerges in the visual and textual user generated content around discussions about Down Syndrome on this specific social media platform. The paper builds upon research on data sciences, cartography of controversies (Venturini, 2010) and enrich these with a reflection on how to apply them to marginalised voices (Klein and D’Ignazio, 2020). The paper proposes to bridge an important theoretical gap between user generated content, digital traces and computational methods. The results showcase an insistent 'infra-humanisation' of the person with Down Syndrome, both visually and textually. Ultimately, the paper proposes a novel methodological framework, data studies to bring to light marginalised and invisible voices in our current digital, increasingly computational, culture

Keywords
computer vision, digital traces, stereotypes, visual narratives