Understanding the Impact of Spatial Immersion in Web Data Stories
November 27, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Seon Gyeom Kim, Juhyeong Park, Yutaek Song, Donggun Lee, Yubin Lee, Ryan Rossi, Jane Hoffswell, Eunyee Koh, Tak Yeon Lee
arXiv ID
2411.18049
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
An increasing number of web articles engage the reader with the feeling of being immersed in the data space. However, the exact characteristics of spatial immersion in the context of visual storytelling remain vague. For example, what are the common design patterns of data stories with spatial immersion? How do they affect the reader's experience? To gain a deeper understanding of the subject, we collected 23 distinct data stories with spatial immersion, and identified six design patterns, such as cinematic camera shots and transitions, intuitive data representations, realism, naturally moving elements, direct manipulation of camera or visualization, and dynamic dimension. Subsequently, we designed four data stories and conducted a crowdsourced user study comparing three design variations (static, animated, and immersive). Our results suggest that data stories with the design patterns for spatial immersion are more interesting and persuasive than static or animated ones, but no single condition was deemed more understandable or trustworthy.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted