Source-linked AI summary
Bringing Data to Life: Designing Data Characters for the Emotional Self
Diego Abarcar Calugay, Isabella Amador, Keke Wu
TL;DR
As journal entries accumulate, identifying affective patterns and comparing experiences becomes difficult, and existing visualizations may miss emotional nuance. This paper explores customizable, human-like Data Characters as affective visualizations; two preliminary walkthroughs found the interface easy to use and customization expressive.
Problem
As journal entries accumulate, identifying affective patterns and comparing experiences is difficult, while existing visualizations can miss context and emotional nuance.
Source: §1 · p. 1Method
Results
In two preliminary anger walkthroughs, both participants found the interface easy to use and said customization enabled personalized, nuanced emotional expression.
Source: §3 · p. 2Takeaways & Limitations
The work highlights anthropomorphism as a promising approach to visualizing affective and experiential data.
Source: §6 · p. 2The evidence is preliminary rather than systematic: walkthroughs involved only two participants representing one emotion.
Source: §5 · p. 2
Abstract
from arXiv · showhide
Journaling is a common practice for emotional expression, reflection, and processing. However, as entries accumulate, it can become difficult to interpret and compare their affective content, especially since traditional text-based analyses and visualizations often struggle to convey affective nuance. We introduce Data Characters, a visualization approach that represents affective content in journaling through human-like characters. Using a customizable Data Character as a design probe, we investigate the potential of character-based representations for conveying affective experiences and explore what visual encodings emerge through customization. Preliminary walkthroughs with two participants demonstrate the intuitiveness and feasibility of the approach. This work contributes an exploratory approach to studying how affective experiences can be visually represented and encoded through anthropomorphic forms.
1 INTRODUCTION
The paper introduces Data Characters, human-like visualizations of journaling’s affective content, and uses a customizable character as a design probe to explore how character features can encode affective experiences. This approach addresses the difficulty of identifying patterns and emotional changes in accumulated entries and the limits of existing text visualizations.
- As journal entries accumulate, identifying affective patterns, comparing experiences, and understanding emotional changes can become difficult.Journaling is widely used to process, regulate, and reflect on emotional experiences.Source: §1 · p. 1
- Existing text visualizations can overlook context and emotional nuance by emphasizing word- or sentence-level features, while thematic coding may oversimplify affective experiences into discrete categories.These limitations motivate visualizations that more directly represent affective content in personal data.Source: §1 · p. 1
- Data Characters represent journaling’s affective content through human-like characters’ facial expressions and body postures, explored through a customizable character used as a design probe.The customization process examines how character features may function as affective visual encodings.Source: §1 · p. 1
2 DESIGN RATIONALE
Data Characters use familiar human-like cues—facial expressions and body posture—to represent affective experiences. The design leaves character features customizable to explore how affective experiences can be represented and what visual encodings emerge.
- Because people naturally communicate emotion through facial expressions and body posture, the design uses familiar human-like cues rather than abstract visual forms.Source: §2 · p. 1
- Prior work suggests anthropomorphism may support emotional expression and interpretation, including through expressive postures and faces and voices that aid understanding of complex instructions.Anthropographics humanize data to elicit empathetic responses, though their effectiveness is contested.Source: §2 · p. 1
- Data Characters represent affective experiences through full-body, human-like characters whose features are customizable rather than mapped to emotions in advance.The study asks how Data Characters can represent affective experiences and what visual encodings emerge through customization.Source: §2 · p. 1
3 DATA CHARACTERS AS A DESIGN PROBE
The study used a customizable, human-like Data Character as a design probe, letting users map affective experiences to facial features and posture. In preliminary walkthroughs, two participants found the interface easy to use and its options enabled personalized, nuanced emotional expression.
3 DATA CHARACTERS AS A DESIGN PROBE
- The Data Character served as a design probe that let users represent affective experiences by manipulating facial features and body posture rather than following prescribed visual mappings.The interface was designed to explore how users choose to encode affect through an anthropomorphic form.Source: §3 · p. 1
- Drawing on the PAD Emotional State Model and Affective Slider, the interface used sliders for facial expressions, including mouth curvature and aperture, eye closure, and eyebrow angle.Sliders interpolated between expressions such as frown and smile.Source: §3 · pp. 1–2
- Drag-and-drop controls let users adjust limb openness and flexion and the orientation and lean of the head and body, using postural cues important to affective expression.The web application was built with Rive, HTML, CSS, and JavaScript; finalized characters could be exported as JSON customization values for subsequent analysis.Source: §3 · p. 2
Preliminary Walkthroughs
- In preliminary walkthroughs, both participants found the interface easy to use and said its customization options enabled personalized, nuanced expressions of “anger.”The walkthroughs assessed interface intuitiveness and feasibility; user-generated visualizations illustrated personalized representations of the same emotion.Source: §3 · p. 2, Figure 2 · p. 2
4 IMPLICATIONS
The implications position Data Characters as a way to visualize affective experience directly in personal text, using familiar anthropomorphic cues and opening a design space for further research. They may also support interpretation and communication of emotional patterns across time and between individuals.
4 IMPLICATIONS
- Data Characters offer an alternative to visualizations focused on lexical, thematic, or statistical properties by making affective experiences themselves visualizable.This provides a way to interact with journal data through its affective content.Source: §4 · p. 2
- Anthropomorphic designs can use familiar cues to express emotion, offering an alternative to abstract visuals.Source: §4 · p. 2
- Data Characters may help communicate and interpret emotional patterns across time and between individuals, including in collaborative and therapeutic settings.Source: §4 · p. 2
- The approach opens a design space for direct affective representation and motivates research into how affect can be visually encoded.Source: §4 · p. 2
5 LIMITATIONS & FUTURE WORK
The paper identifies limits in the preliminary evaluation, the generalizability and intuitiveness of character-based affective representations, and their omission of emotional context. Future work could broaden the study and explore alternative or combined representations.
5 LIMITATIONS & FUTURE WORK
- Two-participant walkthroughs offered initial evidence of feasibility and intuitiveness, not a systematic evaluation; a larger design-probe study will examine varied affective experiences and emerging encoding strategies.The authors also identify open questions about the scope and boundaries of Data Characters.Source: §5 · p. 2
- Nonverbal expressions may not convey affect universally, so future work should examine how user-generated representations are interpreted across individuals and cultures.Source: §5 · p. 2
- Anthropomorphizing emotions may not feel intuitive or expressive for everyone, motivating investigation of alternatives such as visual metaphors [8].Source: §5 · p. 2
- The system focuses on affect without representing its broader context, including interactions, relationships, and events; future work could represent affective and contextual information together.Source: §5 · p. 2
6 CONCLUSION
The paper introduces Data Characters, an exploratory approach to representing affective content in journaling through anthropomorphic forms.
6 CONCLUSION
- Data Characters use customizable human-like characters to represent affective content in journaling.The approach uses a customizable Data Character as a design probe.Source: §6 · p. 2
- Facial and bodily features may serve as affective visual encodings, making anthropomorphism a promising approach to visualizing affective and experiential data.Source: §6 · p. 2
3 DESIGN PROBE
The design probe uses customizable human-like characters to represent affect through facial and bodily features. The paper discusses their potential, limitations, and directions for further study.
3 DESIGN PROBE
- Users generated personal visualizations of “anger” by customizing a Data Character’s facial and bodily features.The probe used sliders for continuous emotional representation and drag-and-drop handles for limb movement.Source: §3 · p. 3, Figure 4 · p. 3
IMPLICATIONS
- Data Characters directly visualize affect and use anthropomorphism to scaffold comprehension of personal data, potentially supporting emotional communication across domains such as psychotherapy.Source: IMPLICATIONS · p. 3
LIMITATIONS
- Nonverbal expressions may not be universal, and characters may capture emotions without the context that enriches affective experiences.Source: LIMITATIONS · p. 3
FUTURE WORK
- Future work will study varied emotional experiences and common encoding strategies, examine cultural differences and visual metaphors, and expand representation to include affective context such as life events.Source: FUTURE WORK · p. 3