Data as Delight: Eating data

Mueller, Florian; Dwyer, Tim; Goodwin, Sarah; Marriott, Kim; Deng, Jialin; Phan, Han Duy; Lin, Jionghao; Chen, Kun-Ting; Wang, Yan; Khot, Rohit Ashok

doi:10.1145/3411764.3445218

Cited by 16 publications

(6 citation statements)

References 79 publications

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“…Specifically, we considered a paper qualified if: (i) it is about data visualization, and (ii) it explicitly mentions emotion or emotion-related words (e.g., surprise, joy) in its keywords, title, abstract, or major findings. As a result, we identified 24 qualified papers [5,7,9,20,26,27,37,44,45,47,48,50,51,53,57,58,62,65,[70][71][72][73][74]94].…”

Section: Methodsmentioning

confidence: 99%

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Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design

Lan

Shi

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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In recent years, more and more researchers have reflected on the undervaluation of emotion in data visualization and highlighted the importance of considering human emotion in visualization design. Meanwhile, an increasing number of studies have been conducted to explore emotion-related factors. However, so far, this research area is still in its early stages and faces a set of challenges, such as the unclear definition of key concepts, the insufficient justification of why emotion is important in visualization design, and the lack of characterization of the design space of affective visualization design. To address these challenges, first, we conducted a literature review and identified three research lines that examined both emotion and data visualization. We clarified the differences between these research lines and kept 109 papers that studied or discussed how data visualization communicates and influences emotion. Then, we coded the 109 papers in terms of how they justified the legitimacy of considering emotion in visualization design (i.e., why emotion is important) and identified five argumentative perspectives. Based on these papers, we also identified 61 projects that practiced affective visualization design. We coded these design projects in three dimensions, including design fields (where), design tasks (what), and design methods (how), to explore the design space of affective visualization design.

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Section: Methodsmentioning

confidence: 99%

“…This task guides people to think, reflect, contemplate, and inspire new thoughts through emotion. For example, EdiPulse [27] (Fig. 3 D) is an edible visualization designed to "provoke critical discourse" about physical activities.…”

Section: What: Design Tasksmentioning

confidence: 99%

Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design

Lan

Shi

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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“…Human-Food Interaction (HFI) researchers have rapidly moved to investigate applications of new and emerging technologies within the context of food. In doing so they have explored myriad technologies and use cases; like robotics for enhanced food preparation in smart kitchens [63,69], 3D printing of food-based rewards for exercise [61] and as a means to experience computational data [51], multi-sensory food interactions that enhance or augment the experience of eating [77,95], and the use of virtual reality (e.g., [7]) and social media [33,35] to enhance social aspects of eating. A comprehensive review of this literature and the potential applications of food technology is beyond the scope of this work; we instead refer the reader to Altarriba Bertran et al [4,5] and Deng et al [40], and here we focus our review on how Human-Computer Interaction (HCI) research has sought to improve health and well-being through technology.…”

Section: Related Workmentioning

confidence: 99%

Design and Evaluation of Technologies for Informed Food Choices

Bomfim

Wong

Liang

et al. 2023

ACM Trans. Comput.-Hum. Interact.

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Technology increasingly mediates our everyday interactions with food, ranging from its production and handling to the experience of preparing and eating it with friends and family. However, it is unclear whether these technologies support decisions conducive to a healthy diet. In this work, we devised the first heuristics for evaluating a technology’s support for food literacy: the interconnected combination of awareness, knowledge, and skills to empower individuals to make informed food choices. We applied an iterative, expert-driven process to derive and refine our heuristics, starting with an established food literacy framework. We then conducted evaluations with Nutrition and HCI experts to show how the heuristics support summative and formative design and evaluations of food-related technologies. We show that the heuristics are valuable design tools, and that they help participants reflect on food literacy challenges. We also discuss tensions between nutrition and HCI best practices.

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“…Data visualization can be influential beyond what is rationally supported by the data itself [22,59]. Visualizations can be emotional [53,65]. The same data can be framed in ways that give rhetorical advantage to some narratives over others [36,53].…”

Section: Visualization and Framing Effectsmentioning

confidence: 99%

Polarizing Political Polls: How Visualization Design Choices Can Shape Public Opinion and Increase Political Polarization

Holder,

Xiong

2023

Preprint

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While we typically focus on data visualization as a tool for facilitating cognitive tasks (e.g. learning facts, making decisions), we know relatively little about their second-order impacts on our opinions, attitudes, and values. For example, could design or framing choices interact with viewers’ social cognitive biases in ways that promote political polarization? When reporting on U.S. attitudes toward public policies, it is popular to highlight the gap between Democrats and Republicans (e.g. with blue vs red connected dot plots). But these charts may encourage social-normative conformity, influencing viewers’ attitudes to match the divided opinions shown in the visualization. We conducted three experiments examining visualization framing in the context of social conformity and polarization. Crowdworkers viewed charts showing simulated polling results for public policy proposals. We varied framing (aggregating data as non-partisan “All US Adults,” or partisan “Democrat” / “Republican”) and the visualized groups’ support levels. Participants then reported their own support for each policy. We found that participants’ attitudes biased significantly toward the group attitudes shown in the stimuli and this can increase inter-party attitude divergence. These results demonstrate that data visualizations can induce social conformity and accelerate political polarization. Choosing to visualize partisan divisions can divide us further.

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Data as Delight: Eating data

Cited by 16 publications

References 79 publications

Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design

Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design

Design and Evaluation of Technologies for Informed Food Choices

Polarizing Political Polls: How Visualization Design Choices Can Shape Public Opinion and Increase Political Polarization

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