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3 - Visually mapping the interplay between pandemic interest groups and ‘the vulnerable’ in newspaper accounts, 2018–2022

Published online by Cambridge University Press:  07 January 2025

Dawn Mannay
Affiliation:
Cardiff University
Alastair Roy
Affiliation:
University of Central Lancashire, Preston
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Summary

Introduction

The COVID- 19 pandemic had an unprecedented impact on society, presenting a valuable potential case study of how media represents a societally important topic. We use a visual mapping approach to illuminate and discuss the patterns that emerge within media narratives and coverage relevant to the COVID- 19 pandemic. Our approach involves the creative analysis of ‘big data’ extracted from media reportage in order to create visually accessible depictions of emerging patterns within the analysis. We analysed the contrasting roles played by ‘vulnerable’ groups, ‘mental health’, and people with ‘underlying conditions’ on the one hand, and social and business interest groups on the other hand, within this manufactured ‘collective imaginary’ (Bouchard, 2017, p 19). We visually exposed their often- conflicting impacts on shared media or policy narratives regarding public health, risk, and policy responses to the COVID- 19 pandemic. The complex interplay of these themes creates an excellent case study for the visualisation of ‘post- truth’ media messaging (Fuller, 2020), expanding on techniques we have previously explored. The creative analysis, and resulting visually engaging presentation of the salient factors, effectively represent the complex interplay of narrative persuasion and policy response across the COVID- 19 pandemic.

This study applied the term frequency and word vector techniques that are common in the ‘big data’ tools that underlie web searches and recommendation algorithms and guide many other aspects of 21st- century life. To make these underlying quantitative data analyses visible and intelligible to a non- mathematical viewer, this chapter uses a range of visual approaches to data representation to portray patterns and findings in an accessible manner. Our objective is to explore the potential within big data analysis to make observable the metadata underlying media narratives and messaging. Creativity is fostered by tools that are easy to use, converting statistical analysis into play and effort into image making. There is a tension between creating imagery with a high impact, in which the message is simplified and amplified into an aesthetic call for action, and the systematic application of statistical techniques. Any resolution of the tension must not misrepresent findings, and at the same time it must recognise the distorting influence of aesthetic choices.

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Publisher: Bristol University Press
Print publication year: 2024

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