Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations
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| Titel: | Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations |
|---|---|
| Autoren: | Carter Blair, Xiyao Wang, Charles Perin |
| Quelle: | IEEE Transactions on Visualization and Computer Graphics. 31:1006-1016 |
| Publication Status: | Preprint |
| Verlagsinformationen: | Institute of Electrical and Electronics Engineers (IEEE), 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | FOS: Computer and information sciences, Cognition and Perception, Computer Sciences, 05 social sciences, Computer Science - Human-Computer Interaction, emotion, 02 engineering and technology, psychology, Social and Behavioral Sciences, Human-Computer Interaction (cs.HC), FOS: Psychology, affect, Graphics and Human Computer Interfaces, Physical Sciences and Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Psychology, 0501 psychology and cognitive sciences, information visualization, H.1.2, visualization |
| Beschreibung: | Emotion is an important factor to consider when designing visualizations as it can impact the amount of trust viewers place in a visualization, how well they can retrieve information and understand the underlying data, and how much they engage with or connect to a visualization. We conducted five crowdsourced experiments to quantify the effects of color, chart type, data trend, data variability and data density on emotion (measured through self-reported arousal and valence). Results from our experiments show that there are multiple design elements which influence the emotion induced by a visualization and, more surprisingly, that certain data characteristics influence the emotion of viewers even when the data has no meaning. In light of these findings, we offer guidelines on how to use color, scale, and chart type to counterbalance and emphasize the emotional impact of immutable data characteristics. |
| Publikationsart: | Article |
| ISSN: | 2160-9306 1077-2626 |
| DOI: | 10.1109/tvcg.2024.3456361 |
| DOI: | 10.17605/osf.io/ywjs4 |
| DOI: | 10.48550/arxiv.2407.18427 |
| Zugangs-URL: | https://pubmed.ncbi.nlm.nih.gov/39255151 http://arxiv.org/abs/2407.18427 |
| Rights: | IEEE Copyright CC BY |
| Dokumentencode: | edsair.doi.dedup.....392f07143e2a70aaf74d128a9caa07d7 |
| Datenbank: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstract: | Emotion is an important factor to consider when designing visualizations as it can impact the amount of trust viewers place in a visualization, how well they can retrieve information and understand the underlying data, and how much they engage with or connect to a visualization. We conducted five crowdsourced experiments to quantify the effects of color, chart type, data trend, data variability and data density on emotion (measured through self-reported arousal and valence). Results from our experiments show that there are multiple design elements which influence the emotion induced by a visualization and, more surprisingly, that certain data characteristics influence the emotion of viewers even when the data has no meaning. In light of these findings, we offer guidelines on how to use color, scale, and chart type to counterbalance and emphasize the emotional impact of immutable data characteristics. |
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| ISSN: | 21609306 10772626 |
| DOI: | 10.1109/tvcg.2024.3456361 |