Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866929438079320064 |
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| author | Blair, Carter Wang, Xiyao Perin, Charles |
| author_facet | Blair, Carter Wang, Xiyao Perin, Charles |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2407_18427 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations Blair, Carter Wang, Xiyao Perin, Charles Human-Computer Interaction H.1.2 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. |
| title | Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations |
| topic | Human-Computer Interaction H.1.2 |
| url | https://arxiv.org/abs/2407.18427 |