This paper presents VisuaLies, a workshop designed to engage citizens in identifying misleading information visualisations (Misinfovis). The workshop aims to validate and enhance the Classification of Misinfovis Situations (CMiS), a classification system for lay citizens to spot the formal characteristics of Misinfovis, which we call ‘Misinfovis Situations’. Conducted with participants of varying educational backgrounds, VisuaLies included activities to assess pre-existing knowledge, familiarise with Misinfovis concepts, classify Misinfovis examples and lead to an updated version of CMiS featuring fewer Situations with more accessible language. This study underscores the importance of involving lay people in recognising and describing Misinfovis with their own words to support the development of inclusive knowledge societies. Future iterations of VisuaLies aim to involve diverse audiences and refine feedback collection methods to further enhance the classification’s effectiveness.

VisuaLies: Towards a Classification of Misinfovis Situations

Aversa, Elena;Mauri, Michele
2024-01-01

Abstract

This paper presents VisuaLies, a workshop designed to engage citizens in identifying misleading information visualisations (Misinfovis). The workshop aims to validate and enhance the Classification of Misinfovis Situations (CMiS), a classification system for lay citizens to spot the formal characteristics of Misinfovis, which we call ‘Misinfovis Situations’. Conducted with participants of varying educational backgrounds, VisuaLies included activities to assess pre-existing knowledge, familiarise with Misinfovis concepts, classify Misinfovis examples and lead to an updated version of CMiS featuring fewer Situations with more accessible language. This study underscores the importance of involving lay people in recognising and describing Misinfovis with their own words to support the development of inclusive knowledge societies. Future iterations of VisuaLies aim to involve diverse audiences and refine feedback collection methods to further enhance the classification’s effectiveness.
2024
Data visualisation, Workshop, Taxonomy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1281173
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