Evidence for a three-factor theory of emotions
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PAD offers a broad framework that captures complex human emotions with just three values, which the authors argue makes it well suited for predicting player experience in games.
“This model provides a comprehensive framework for capturing the complexity of human emotions using only three dimensional values, making it highly suitable for predicting player experiences in games.”
From Generating Game Levels by Defining Player Experiences (2024) · cites this paper as Russell and Mehrabian 1977
PAD represents emotion using three continuous axes: Pleasure, Arousal, and Dominance.
“The PAD model describes emotions along three continuous dimensions: Pleasure (P), Arousal (A), and Dominance (D).”
From Generating Game Levels by Defining Player Experiences (2024) · cites this paper as Russell and Mehrabian 1977
Another popular approach is to place a particular emotion into a space having a limited set of dimensions including valence, activation, and control.
“Another popular approach is to place a particular emotion into a space having a limited set of dimensions [15], [16], [17]. These dimensions include valence (how pleasent or unpleasent a feeling is) activation2 (how likely is the person to take action under the emotional state) and control (the sense of control over the emotion).”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [16]
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Prime theory: An integrated view of motivation and emotion.
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Self-citationAffective computing with primary and secondary emotions in a virtual human
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When a Car Makes You Smile: Development and Application of an Instrument to Measure Product Emotions
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The influence of emotion, locus of emotion and familiarity upon preference in music
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The development and validation of sensory and emotional scales of touch perception
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The measurement of core affect: A Swedish self‐report measure derived from the affect circumplex
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How Is Your User Feeling? Inferring Emotion Through Human-Computer Interaction Devices1
Hibbeln, M. T., Jenkins, J. L., Schneider, C., Valacich, J. S., & Weinmann, M. (2017) · MIS Quarterly · doi:10.25300/misq/2017/41.1.01 · Cited by 181 · see citing works
- Authors
- Russell, J. A., & Mehrabian, A.
- Affiliations
- University of British Columbia (CA)
- University of California, Los Angeles (US)
- Corresponding author
- Russell, James A
- ORCID
- Russell, James A
- Venue
- Journal of Research in Personality
- Publisher
- Elsevier BV
- Published
- 1977-09
- Volume
- 11
- Issue
- 3
- Pages
- 273-294
- ISSN
- 0092-6566 (ISSN-L)
- OpenAlex
- W2003653478
- Cited by
- 1,940
- References
- 35
- Citations by year
- 2026: 75 · 2025: 112 · 2024: 135 · 2023: 128 · 2022: 169 · 2021: 118 · 2020: 98 · 2019: 91 · 2018: 84 · 2017: 89 · 2016: 74 · 2015: 86 · 2014: 72 · 2013: 74 · 2012: 60
- FWCI
- 22.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Research in Personality (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Emotions and Moral Behavior
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- arousal, emotional state, acquiescence bias, semantic differential, definition of emotion
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