Visual Models for Social Media Image Analysis: Groupings, Engagement, Trends, and Rankings

Authors

  • Gabriele Colombo King’s College London, UK Politecnico di Milano Università IUAV di Venezia
  • Liliana Bounegru King’s College London
  • Jonathan Gray King’s College London

Keywords:

visual methods, social media, digital methods, data visualization, image analysis

Abstract

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.

Author Biographies

Gabriele Colombo, King’s College London, UK Politecnico di Milano Università IUAV di Venezia

PhD in Design, Politecnico di Milano, Gabriele Colombo is affiliated with DensityDesign, a research lab at the Design Department of Politecnico di Milano, and with the Department of Architecture and Arts of the Università IUAV di Venezia. Since 2019 he has been Adjunct Professor at Politecnico di Milano, where he teaches ‘Digital Methods and Communication Design’ in the Communication Design Master Degree. He is part of the Visual Methodologies Collective at the Amsterdam University of Applied Sciences, and he is a member of the Public Data Lab. His research and teaching activities focus on the design of novel strategies for the communication, exploration, analysis and valorisation of collections of images and videos.

Liliana Bounegru, King’s College London

Liliana Bounegru is Lecturer in Digital Methods at the Department of Digital Humanities, King’s College London. Previously she was a postdoctoral research fellow at the Oxford Internet Institute (University of Oxford). Since 2013 she has been a researcher at the Digital Methods Initiative (University of Amsterdam), where she also acted as Managing Director between 2014 and 2016. She obtained her double PhD degree (cum laude) from the University of Groningen and Ghent University. Prior to that she studied at the University of Amsterdam and the University of Bucharest. She co-founded the Public Data Lab, a network of research labs which seeks to facilitate research, democratic engagement and public debate around the future of the data society.

Jonathan Gray, King’s College London

Jonathan Gray is Senior Lecturer in Critical Infrastructure Studies at the Department of Digital Humanities, King’s College London, where he is currently writing a book on data worlds. He is also Cofounder of the Public Data Lab; and Research Associate at the Digital Methods Initiative (University of Amsterdam) and the médialab (Sciences Po, Paris). More about his work can be found at jonathangray.org and he tweets at @jwyg.

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Published

2023-02-26

Issue

Vol. 17 (2023)

Section

Articles

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