Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations.


Journal

IEEE transactions on visualization and computer graphics
ISSN: 1941-0506
Titre abrégé: IEEE Trans Vis Comput Graph
Pays: United States
ID NLM: 9891704

Informations de publication

Date de publication:
15 Apr 2024
Historique:
medline: 15 4 2024
pubmed: 15 4 2024
entrez: 15 4 2024
Statut: aheadofprint

Résumé

People routinely rely on data to make decisions, but the process can be riddled with biases. We show that patterns in data might be noticed first or more strongly, depending on how the data is visually represented or what the viewer finds salient. We also demonstrate that viewer interpretation of data is similar to that of 'ambiguous figures' such that two people looking at the same data can come to different decisions. In our studies, participants read visualizations depicting competitions between two entities, where one has a historical lead (A) but the other has been gaining momentum (B) and predicted a winner, across two chart types and three annotation approaches. They either saw the historical lead as salient and predicted that A would win, or saw the increasing momentum as salient and predicted B to win. These results suggest that decisions can be influenced by both how data are presented and what patterns people find visually salien.

Identifiants

pubmed: 38619945
doi: 10.1109/TVCG.2024.3388515
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Classifications MeSH