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

Fuente: arXiv
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Autores principales: Bearfield, Cindy Xiong, van Weelden, Lisanne, Waytz, Adam, Franconeri, Steven
Formato: Preprint
Publicado: 2024
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author Bearfield, Cindy Xiong
van Weelden, Lisanne
Waytz, Adam
Franconeri, Steven
author_facet Bearfield, Cindy Xiong
van Weelden, Lisanne
Waytz, Adam
Franconeri, Steven
contents 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 salient.
format Preprint
id arxiv_https___arxiv_org_abs_2401_09289
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations
Bearfield, Cindy Xiong
van Weelden, Lisanne
Waytz, Adam
Franconeri, Steven
Human-Computer Interaction
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 salient.
title Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations
topic Human-Computer Interaction
url https://arxiv.org/abs/2401.09289