Name
Title | ||
|---|---|---|
Identifying Emotion through Implicit and Explicit Measures: Cultural Differences, Cognitive Load, and Immersion |
Abstract | ||
|---|---|---|
Measures of emotion should accurately characterize the nature of an emotional experience and determine whether that experience is universal or unique to a subgroup or culture. We investigated the value of assessing emotion through skin conductance (an easy-to-interpret physiological measure) and sliders (frequently used and direct measures of perceived emotion). This paper describes findings from two experiments. The first evaluated various slider configurations and found that measured emotions successfully characterized the emotional nature of short videos. The second experiment collected the slider and skin conductance measures of emotion while one sample of Japanese participants and another sample of Canadian participants viewed longer videos. The measures were sensitive enough to identify cultural differences consistent with existing literature and were also able to identify parts of the experience where members from different cultures reacted consistently, pinpointing content that provoked a universal experience. We offer a toolkit of data interpretation techniques to gain more insight into the implicit and explicit emotion data: analyses for expressiveness and agreement that can infer states such as engagement and fatigue. We summarize the aspects of our measurement approach and toolkit in a model: the ability to distinguish the emotional nature of stimuli, individuals, and affective interaction. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/T-AFFC.2011.36 | T. Affective Computing |
Keywords | Field | DocType |
emotional experience,various slider configuration,universal experience,explicit emotion data,skin conductance measure,explicit measures,identifying emotion,data interpretation technique,emotional nature,cognitive load,skin conductance,canadian participant,cultural differences,measured emotion,data analysis,prototypes,human factors,cognition,computer model,data interpretation,human centered computing,skin,physiology,computational modeling | Social psychology,Data interpretation,Psychology,Cultural diversity,Human-centered computing,Artificial intelligence,Stimulus (physiology),Cognition,Affect (psychology),Cognitive load,Machine learning,Expressivity | Journal |
Volume | Issue | ISSN |
3 | 2 | 1949-3045 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Danielle Lottridge | 1 | 168 | 15.64 |
| Mark Chignell | 2 | 1159 | 153.58 |
| Michiaki Yasumura | 3 | 266 | 36.88 |