Designing for Rich Collocated Social Interactions in the Age of Smartphones
May 22, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
HΓΌseyin UΔur GenΓ§
arXiv ID
2405.13465
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
The quality of social interaction is crucial for psychological and physiological health. Previous research shows that smartphones can negatively impact face-to-face social interactions. Many HCI studies have addressed this by limiting smartphone use during social interactions. While these studies show a decrease in smartphone use, restrictive approaches have their drawbacks. Users need high levels of self-regulation to follow them, and they may cause unintended effects like withdrawal symptoms. Given the impact of smartphones on social interactions, both positive and negative, new solutions are needed to reduce the negative effects of excessive smartphone use without resorting to restrictive methods. This thesis aims to explore smartphone use behavior in the context of social interactions and relationships using various data collection techniques to understand how this behavior hinders and supports social interactions. We began with in situ observations and focus group sessions. Based on insights from these steps, we developed two research prototypes to improve social interactions without restricting smartphone use. We gathered user feedback, reactions, and concerns about these prototypes through user studies. Finally, we evaluated how these prototypes affected conversation quality in social interactions through an experimental user study. This thesis contributes to the field of digital well-being by offering user insights, design implications, and approaches that can guide the creation of solutions to enhance social interactions in the presence of smartphones.
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