Title :

Data visualization in shaping the institutional COVID-19 narrative

Author(s) :

Ferrari, Giovannipaolo [Auteur]
Università degli Studi di Salerno = University of Salerno [UNISA]
Centre de Recherche "Individus Epreuves Sociétés" - ULR 3589 [CeRIES]
Diana, Paolo [Auteur]
Università degli Studi di Salerno = University of Salerno [UNISA]

Journal title :

Society Register

Pages :

69-98

Publication date :

2024-09-26

English keyword(s) :

misrepresentation of data COVID-19 data visualization Italy post-truth
misrepresentation of data
COVID-19
data visualization
Italy
post-truth

HAL domain(s) :

Sciences de l'Homme et Société/Linguistique
Sciences de l'Homme et Société/Sociologie
Sciences de l'Homme et Société/Méthodes et statistiques

English abstract : [en]

This article examines the distortion of data and its visualization in the context of Covid-19 in Italy. While data visualization has become prevalent across various scientific disciplines, it often suffers from being overly ...
Show more >This article examines the distortion of data and its visualization in the context of Covid-19 in Italy. While data visualization has become prevalent across various scientific disciplines, it often suffers from being overly intricate, inappropriate for the data type, or capable of causing perceptual biases and data falsification. The surplus of digital data and its subsequent visualization can lead to the manipulation of information, crafting narratives that diverge from official communications and aim to undermine their credibility and accuracy. This article highlights the necessity for properly disseminating data literacy and investigates data visualization’s epistemological and methodological dimensions, focusing specifically on the Italian scenario. Misrepresentation of COVID-19 data is characterized by the distortion and misrepresentation of the pandemic data collected, processed, and presented. Through an empirical case study, the article underscores the imperative to develop and utilize data visualization techniques that faithfully and accurately depict data.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche "Individus Epreuves Sociétés" (CeRIES) - ULR 3589

Source :

Harvested from HAL

Submission date :

2024-10-04T05:35:44Z