Fermo, sorridi, clicca! Etnografia visuale nell’epoca dei big (visual) data
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The quantity of images created and used has constantly grown in recent years. Numerous images and videos are shared and manipulated every second through social media as private yet public representations of contemporary culture. Despite the interesting role of such images, social and computer scientists alike are still looking for methods and tools for analysing this visual stream and for efficiently connecting visual analytics with their physical and contextualized meanings. Big visual data is a crucial challenge. It demands new research skills to intertwine computational data – numerous images, tags, places, likes, etc. – with qualitative data, such as the images’ context, users’ intentions, and the invisible audiences. This article analyses two large-scale studies that merged quantitative computational methods with qualitative ones: Phototrails.net and Selfiecities. net. Those studies used a multi-method approach to combine macro-analyses (e.g. of an entire city’s ‘urban visual style’) with micro-analyses (e.g. meanings and specificity of each photo in the sample). They also devised new information-display solutions, which provide both an innovative way of representing the results and a specific epistemological approach for interpreting them. Starting from these case studies, the paper focuses on a semi-automated methodology that codifies and analyses images from three different perspectives: authors, subjects and commenters. This method contributes to a significant new understanding of user-generated images as stratified, multi-perspective – and often conflictual – social representations.
Towards the Platformization of (Social) Media Memory: Articulating Archive, Assemblage, and Ephemerality
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