Affective Appraisal Data for Virtual Environments with Ambient Odor

Aggregating experimental data from a study investigating the effect of ambient odor on affective appraisal of a desktop virtual environment with signs of public disorder. The study involved participants exploring a virtual suburban neighborhood while exposed to pleasant, unpleasant, or no ambient odor, reporting safety concerns and affective feelings. The dataset is associated with research published in 2020 by Alexander Toet.

Use Cases

• Analyze reported safety concerns and affective feelings associated with signs of crime in the virtual environment.
• Compare participant responses across the three ambient odor conditions (tar, cut grass, no odor) for signs of neglect and vandalism.
• Investigate the relationship between safety-related concerns and affective connotations for different types of social disorder cues.

Strengths

• Dataset is published under a permissive CC0 1.0 license, allowing for broad reuse.
• Research is focused on a specific experimental design testing ambient odor in virtual environments, providing targeted data.
• Data is associated with a peer-reviewed study published in 2020.

Limitations

• The specific data structure, column names, and row count are not provided in the input, limiting initial assessment.
• The study concluded no significant effect of odor, which may limit its utility for modeling odor-based affective modulation.
• Sample size and demographic details of the participant pool are not specified, which could affect generalizability.

Provenance

Source

Dryad digital repository.

Collection Method

Experimental data collected from participants exploring a desktop virtual environment and reporting on safety concerns and affective feelings.

Freshness

Data was last updated in 2020.