How can generative soundscape composition enable different perspectives on forests in an era of planetary crisis? The forestscapes listening lab explores how sound can serve as a medium for collective inquiry into forests as living cultural landscapes.
The soundscapes are composed with folders of sound from different sources, including field recordings from researchers, sound artists and forest practitioners, as well as online sounds from the web, social media and sound archives. They are composed using custom scripts with the open source supercollider software as well as open source norns device, a “sound machine for the exploration of time and space”.
With social media image analysis, one collects and interprets online images for the study of topical affairs. This analytical undertaking requires formats for displaying collections of images that enable their inspection. First, we discuss features of social media images to make a case for studying them in groups (rather than individually): multiplicity, circulation, modification, networkedness, and platform specificity. In all, these offer reasons and means for an approach to social media image research that privileges the collection of images as its analytical object. Second, taking the 2019 Amazon rainforest fires as a case study, we present four visual models for analyzing collections of social media images. Each visual model matches a distinctive spatial arrangement with a type of analysis: grouping images by theme with clusters, surfacing dominant images and their engagement with treemaps, following image trends with plots, and comparing image rankings across platforms with grids.
The TANTLab is hosting a virtual panel on Jan 25 (5.30 CET) where Public Data Lab members Tommaso Venturini and David Moats will participate together with Laura Nelson from University of British Columbia. The theme of the panel is whether the influx of computational methods challenges ingrained epistemic binaries in SSH. We define an epistemic binary as a dichotomy that (perhaps artificially) separates knowledge production into different kinds.
The panel is arranged as part of the process of editing the forthcoming ‘handbook of digital and computational SSH’ (edited by Public Data Lab members Anders Koed Madsen & Anders Kristian Munk on Edward Elgar). Each of the three authors discuss such binaries in their chapters and this panel brings them together to reflect more broardly on the fate of binaries in contemporary digital knowledge production.