Investigation of the Effect of Incidental Fear Privacy Behavioral Intention (Technical Report)
July 16, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Uchechi Phyllis Nwadike, Thomas GroΓ
arXiv ID
2007.08604
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Background. Incidental emotions users feel during their online activities may alter their privacy behavioral intentions. Aim. We investigate the effect of incidental affect (fear and happiness) on privacy behavioral intention. Method. We recruited $330$ participants for a within-subjects experiment in three random-controlled user studies. The participants were exposed to three conditions \textsf{neutral}, \textsf{fear}, \textsf{happiness} with standardised stimuli videos for incidental affect induction. Fear and happiness were assigned in random order. The participants' privacy behavioural intentions (PBI) were measured followed by a Positive and Negative Affect Schedule (PANAS-X) manipulation check on self-reported affect. The PBI and PANAS-X were compared across treatment conditions. Results. We observed a statistically significant difference in PBI and Protection Intention in neutral-fear and neutral-happy comparisons. However across fear and happy conditions, we did not observe any statistically significant change in PBI scores. Conclusions. We offer the first systematic analysis of the impact of incidental affects on Privacy Behavioral Intention (PBI) and its sub-constructs. We are the first to offer a fine-grained analysis of neutral-affect comparisons and interactions offering insights in hitherto unexplained phenomena reported in the field.
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