Meaningful play and malicious delight: Exploring maldaimonic game UX
October 07, 2023 Β· Declared Dead Β· π ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Katie Seaborn, Satoru Iseya
arXiv ID
2310.04733
Category
cs.HC: Human-Computer Interaction
Citations
2
Venue
ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play
Last Checked
4 months ago
Abstract
Maldaimonia is a new experiential concept that refers to self-actualization and self-expression through egocentric, destructive, and/or exploitative activities. Still, it is unclear whether maldaimonia is an actual facet of real experience. As a subversive orientation, it may be rare or socially challenging to discuss openly. However, video games provide a space in which people can be expressive in different ways without the same repercussions as in real life. Indeed, game spaces may be one of the few contexts in which to study maldaimonic experiences. In this study, we examined whether and how maldaimonia exists as a feature of game user experiences by analyzing critical self-reports of gaming activities, confirming its existence. We contribute this new construct to work on "dark play" in games research.
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