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Social Signal Processing in Affective Virtual Reality: Human-Shaped Agents Increase Electrodermal Activity in an Elicited Negative Environment.
- Source :
-
CyberPsychology, Behavior & Social Networking . Apr2024, Vol. 27 Issue 4, p268-274. 7p. - Publication Year :
- 2024
-
Abstract
- Prior research on affect elicitation indicates that stimuli with social content (pictures or videos) are more arousing than nonsocial stimuli. In particular, they elicit stronger physiological arousal as measured by electrodermal activity (EDA; i.e., social EDA effect). However, it is unclear how this effect applies to virtual reality (VR), which enables an enhanced sense of presence (SoP) and ecological validity. The study here approached this question from a social–emotional VR framework. A sample of N = 72 participants (55 percent women) experienced a set of six virtual environments (VEs) in the form of emotional parks specifically designed to elicit positive, negative, or neutral affectivity. Half of these VEs included human-shaped agents (social context) and the other half omitted these agents (nonsocial context). The results supported the social EDA effect, which in addition was amplified by the reported SoP. Importantly, the VE featuring a social negative content qualified this observed social EDA effect. The finding is discussed in the light of a negativity bias reported in affect literature, through which negative stimuli typically mobilize attention and bodily activation as a mechanism linked to stress responses. The study's implications extend to the use of VR in both research and practical applications, emphasizing the role of social content in influencing affective and physiological responses. [ABSTRACT FROM AUTHOR]
- Subjects :
- *STATISTICAL models
*ECOLOGY
*RESEARCH funding
*COMPUTER software
*PUBLIC buildings
*DATA analysis
*SKIN physiology
*HUMANITY
*QUESTIONNAIRES
*EMOTIONS
*DESCRIPTIVE statistics
*SIGNAL processing
*VIRTUAL reality
*ATTENTION
*SOCIAL skills
*PSYCHOLOGICAL stress
*STATISTICS
*AFFECT (Psychology)
*DATA analysis software
*CONFIDENCE intervals
Subjects
Details
- Language :
- English
- ISSN :
- 21522715
- Volume :
- 27
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- CyberPsychology, Behavior & Social Networking
- Publication Type :
- Academic Journal
- Accession number :
- 176780848
- Full Text :
- https://doi.org/10.1089/cyber.2023.0273