Digital Methods Summer School and Data Sprint 2024
The Digital Methods Initiative (DMI), Amsterdam, is holding its annual Summer School on 'Visual methods: From platform aesthetics and data visualisation to AI hermeneutics'. The format is that of a (social media and web) data sprint, with tutorials as well as hands-on work for telling stories with data. There is also a programme of keynote speakers. It is intended for advanced Master's students, PhD candidates and motivated scholars who would like to work on (and complete) a digital methods project in an intensive workshop setting. For a preview of what the event is like, you can view short video clips from previous editions of the School.
From platform aesthetics and data visualisation to AI hermeneutics
The application of visual methods to online culture has swung between the hermeneutical tradition of interpretation to the formalisms of visualisation and, most recently, to the question of how to interpret generated images. In the interpretative tradition, platforms have visual styles that are carried forward when one posts. There may be a dominant aesthetic that then is extolled in the comments and scoring systems. For example, the term 'Instagramism' captures a 'look' or mise-en-scène associated with the platform, and how well one performs it is reflected in comment space, together with the metrics. Platforms may have preferred communicative styles and means of expression such as memes and emoji. The style is also an affordance aesthetic, where one's knowledge of platform vernacular is displayed in a post that maintains a thread or in a well chosen reaction that closes it. These posts, comments, reactions, replies, threads, and conversation stoppers are also datapoints which depending on their combination and other meta would be visualised in specific manners. Learning to visualise (and when to visualise) are central to visual methods for the study of online data and images. Collections of images may be visualised or they may be datified and then visualised. Most recently, the study of image generation by AI platforms has multiple points of departure. Computational hermeneutics, or the analysis of the histories and styles extended in computational outputs, focuses on how the visual is the product of certain algorithms, models and/or architectures. For example, in AI hermeneutics there are outputs that one may discern through the model of generation such as diffusion or 'style transfer'. The Summer School takes up questions of how to study current visual platform aesthetics and affordances, online data visualisation, image collections, datafied images as well as generative AI image outputs. The first week has as its focus visual methods for visual data and interpreting AI; among the specific focal points are large (and small) image collections. The second week highlights visual platform affordances, taking up the study of different platform types, e.g., the post-and-comment platform as well as the tweet-and-reply space with threads.