Studies in Communication Sciences (May 2024)

Images, clusters and types – Making sense of (large) image corpora and related practices in and with digital media

  • Wolfgang Reißmann,
  • Ulla Autenrieth,
  • Rebecca Venema

DOI
https://doi.org/10.24434/j.scoms.2024.01.5243
Journal volume & issue
Vol. 24, no. 1
pp. 29 – 34

Abstract

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In November 2021, the Visual Communication Division of the German Communication Association (DGPuK) celebrated its 20th anniversary at the University of Trier with a one-year pandemic delay. Marion G. Müller, Katharina Christ and Christof Barth organized an excellent conference to mark the occasion and to reflect on past and current trends, topics, and challenges in visual communication research. Resuming the thematic scope of the division’s first conference held in Hamburg in 2000, the conference focused on “The power of images – Images of power. On visual political communication in digital contexts.” While analyses of press photography in the tradition of political iconology were the main approaches twenty years ago, the program of the anniversary conference demonstrated diversified thematic foci and methodological approaches. The presentations examined a broad range of visual digital media and visual communication exerted by various actors ranging from the press to politicians to activists and citizens. Concurrently, we also saw a considerable diversity concerning methodological approaches and a rising influence of computational methods for analyzing the increasingly large numbers of images in digital media environments. With the panel “Image type / image cluster analysis as an approach to analyzing large numbers of images in online environments,” a discussion on diverse methodological approaches and their potentials and challenges among our members started. After the conference, we decided to open up our internal discussion and reach out to international colleagues working on similar questions. The long-term result is this Thematic Section on diverse methods for structuring image data corpora drawing on different traditions of visual analysis.

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