The DOI matches its Crossref record; 31 of the 35 references it cites were found in a registry or an index.
Evidence for a three-factor theory of emotions
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“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
In the citing paper
“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
In the citing paper
“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]
Citations
Cites
Statistical principles in experimental design.
Winer, B. J. (1962) · McGraw-Hill Book Company · doi:10.1037/11774-000 · Cited by 27,137
(1970) · Cited by 24,983
Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957) · Cited by 9,433
(1974) · Medical Entomology and Zoology · Cited by 7,295
Self-citationConflict, arousal, and curiosity.
Berlyne, D. E. (1960) · McGraw-Hill Book Company · doi:10.1037/11164-000 · Cited by 6,018
The theory of the estimation of test reliability
Kuder, G. F., & Richardson, M. W. (1937) · Psychometrika · doi:10.1007/bf02288391 · Cited by 1,953
Linear models in decision making.
Dawes, R. M., & Corrigan, B. (1974) · Psychological Bulletin · doi:10.1037/h0037613 · Cited by 1,887
Cross-Cultural Universals of Affective Meaning
Carroll, J. B., Osgood, C. E., May, W. H., & Miron, M. S. (1976) · The American Journal of Psychology · doi:10.2307/1421762 · Cited by 1,154
Schlosberg, H. (1954) · Psychological Review · doi:10.1037/h0054570 · Cited by 1,096
(2007) · Springer eBooks · doi:10.1007/978-3-540-76516-5_4 · Cited by 792
Research works printed but not linked: 2
- Mehrabian, 1972, Nonverbal communication, Vol. 19
- Mehrabian, 1975, Environmental effects on affiliation among strangers, Humanitas, 11, 219
Cited by
Sorted by citations
Items 201–300 of 1,002
Out of the Lab and into the Fray: Towards Modeling Emotion in Everyday Life
Healey, J., Nachman, L., Subramanian, S., Shahabdeen, J., & Morris, M. E. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12654-3_10 · Cited by 95
Multi-Modal Recurrent Attention Networks for Facial Expression Recognition
Lee, J., Kim, S., Kim, S., & Sohn, K. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2996086 · Cited by 100
A Survey on Physiological Signal-Based Emotion Recognition
Ahmad, Z., & Khan, N. (2022) · Bioengineering · doi:10.3390/bioengineering9110688 · Cited by 99
Puccinelli, N. M., Wilcox, K., & Grewal, D. (2014) · Journal of Marketing · doi:10.1509/jm.13.0026 · Cited by 95
Poels, K., van den Hoogen, W. M., IJsselsteijn, W. A., & de Kort, Y. A. W. (2011) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2010.0040 · Cited by 95
Keib, K. M., Espina, C., Lee, Y.-I., Wojdynski, B. W., Choi, D., & Bang, H. (2017) · Media Psychology · doi:10.1080/15213269.2017.1378108 · Cited by 105
Attention to Television: Alpha Power and Its Relationship to Image Motion and Emotional Content
Simons, R. F., Detenber, B. H., Cuthbert, B. N., Schwartz, D. D., & Reiss, J. E. (2003) · Media Psychology · doi:10.1207/s1532785xmep0503_03 · Cited by 96
Voice emotion perception and production in cochlear implant users
Jiam, N. T., Caldwell, M. T., Deroche, M. L. D., Chatterjee, M., & Limb, C. J. (2017) · Hearing Research · doi:10.1016/j.heares.2017.01.006 · Cited by 93
Soleymani, M., Chanel, G., Kierkels, J. J. M., & Pun, T. (2008) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism.2008.14 · Cited by 92
Hospitality servicescape effects on customer-employee interactions: A multilevel study
Kaminakis, K., Karantinou, K., Koritos, C., & Gounaris, S. P. (2018) · Tourism Management · doi:10.1016/j.tourman.2018.11.013 · Cited by 101
Survey on visual sentiment analysis
Ortis, A., Farinella, G. M., & Battiato, S. (2020) · IET Image Processing · doi:10.1049/iet-ipr.2019.1270 · Cited by 92
Behavioral and emotional consequences of brief delays in human–computer interaction
Szameitat, A. J., Rummel, J., Szameitat, D. P., & Sterr, A. (2009) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2009.02.004 · Cited by 92
Affective information processing and the assessment of anxiety
Lang, P. J., & Cuthbert, B. N. (1984) · Journal of Psychopathology and Behavioral Assessment · doi:10.1007/bf01321326 · Cited by 92
AI Based Emotion Detection for Textual Big Data: Techniques and Contribution
Kusal, S., Patil, S., Kotecha, K. V., Aluvalu, R., & Vijayakumar, V. (2021) · Big Data and Cognitive Computing · doi:10.3390/bdcc5030043 · Cited by 105
A perceptual model of smellscape pleasantness
Xiao, J., Tait, M., & Kang, J. (2018) · Cities · doi:10.1016/j.cities.2018.01.013 · Cited by 90
Speech emotion recognition approaches: A systematic review
Hashem, A., Arif, M., & Alghamdi, M. (2023) · Speech Communication · doi:10.1016/j.specom.2023.102974 · Cited by 106
A data-driven classification of feelings
Thomson, D. M. H., & Crocker, C. (2012) · Food Quality and Preference · doi:10.1016/j.foodqual.2012.09.002 · Cited by 95
Ritz, T., & Steptoe, A. (2000) · Psychosomatic Medicine · doi:10.1097/00006842-200011000-00011 · Cited by 90
Influence of music liking on EEG based emotion recognition
Daimi, S. N., & Saha, G. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102251 · Cited by 93
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era
Triantafyllopoulos, A., Schuller, B. W., İymen, G., Sezgin, T. M., He, X., Yang, Z., Tzirakis, P., Liu, S., Mertes, S., André, E., et al. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3250266 · Cited by 102
Zerbe, W. J., Dobni, D. M., & Harel, G. H. (1998) · Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · doi:10.1111/j.1936-4490.1998.tb00160.x · Cited by 89
Perceived Gesture Dynamics in Nonverbal Expression of Emotion
Dael, N., Goudbeek, M. B., & Scherer, K. R. (2013) · Perception · doi:10.1068/p7364 · Cited by 88
Online shopping environments in fashion shopping: An S-O-R based review
Kawaf, F., & Tagg, S. (2012) · The Marketing Review · doi:10.1362/146934712x13366562572476 · Cited by 117
Lottridge, D. M., Chignell, M., & Jovičić, A. (2011) · Reviews of Human Factors and Ergonomics · doi:10.1177/1557234x11410385 · Cited by 89
How Are You Feeling? Revisiting the Quantification of Emotional Qualia
Kron, A., Goldstein, A., Lee, D. H.-J., Gardhouse, K., & Anderson, A. K. (2013) · Psychological Science · doi:10.1177/0956797613475456 · Cited by 104
Affective ranking of movie scenes using physiological signals and content analysis
Soleymani, M., Chanel, G., Kierkels, J. J. M., & Pun, T. (2008) · doi:10.1145/1460676.1460684 · Cited by 88
What a Feeling: The Role of Immediate and Anticipated Emotions in Risky Decisions
Schlösser, T. M., Dunning, D. A., & Fetchenhauer, D. (2011) · Journal of Behavioral Decision Making · doi:10.1002/bdm.757 · Cited by 96
Hedonic asymmetry in emotional responses to consumer products
Schifferstein, H. N. J., & Desmet, P. (2010) · Food Quality and Preference · doi:10.1016/j.foodqual.2010.07.004 · Cited by 89
Embodied Conversational Agents on a Common Ground
Ruttkay, Z., Dormann, C., & Noot, H. (2004) · Human-computer interaction series · doi:10.1007/1-4020-2730-3_2 · Cited by 86
Understanding Emotional Response Theory: The Role of Instructor Power and Justice Messages
Horan, S. M., Martin, M. M., & Weber, K. (2012) · Communication Quarterly · doi:10.1080/01463373.2012.669323 · Cited by 86
EmotionCues : Emotion-Oriented Visual Summarization of Classroom Videos
Zeng, H., Shu, X., Wang, Y., Wang, Y., Zhang, L., Pong, T.-C., & Qu, H. (2020) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2019.2963659 · Cited by 86
Introduction to Human Affective Neuroscience
Armony, J. L., & Vuilleumier, P. O. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9780511843716.003 · Cited by 96
WASABI: affect simulation for agents with believable interactivity
Becker-Asano, C. (2008) · Cited by 86
Analysis of personality measures in terms of basic dimensions of temperament.
Mehrabian, A., & O'Reilly, E. (1980) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.38.3.492 · Cited by 86
Self-citationExploring new formats of the Self-Assessment Manikin in the design with children
Hayashi, E. C. S., Posada, J. E. G., Maike, V. R. M. L., & Baranauskas, M. C. C. (2016) · Brazilian Symposium on Human Factors in Computing Systems (IHC) · doi:10.1145/3033701.3033728 · Cited by 88
Emotion recognition based on customized smart bracelet with built-in accelerometer
Zhang, Z., Song, Y., Cui, L., Liu, X., & Zhu, T. (2016) · PeerJ · doi:10.7717/peerj.2258 · Cited by 94
Crowdsourcing for Affective Annotation of Video: Development of a Viewer-reported Boredom Corpus
Soleymani, M., & Larson, M. (2010) · Archive ouverte UNIGE (University of Geneva) · Cited by 84
Consumer preferences in the design of airport passenger areas
van Oel, C. J., & den Berkhof, F. W. V. (2013) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2013.08.005 · Cited by 84
The Emotional Significance of Color in Television Presentations
Detenber, B. H., Simons, R., & Reiss, J. E. (2000) · Media Psychology · doi:10.1207/s1532785xmep0204_02 · Cited by 77
Continuous emotion detection in response to music videos
Soleymani, M., Koelstra, S., Patras, I., & Pun, T. (2011) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2011.5771352 · Cited by 84
The Structure and Intensity of Emotional Experiences: Method and Context Convergence
Mano, H. (1991) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2603_1 · Cited by 84
Thorson, E., Christ, W. G., & Caywood, C. L. (1991) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838159109364141 · Cited by 84
Normal-Hearing Listeners’ and Cochlear Implant Users’ Perception of Pitch Cues in Emotional Speech
Gilbers, S., Fuller, C. D., Gilbers, D., Broersma, M., Goudbeek, M. B., Free, R. H., & Başkent, D. (2015) · i-Perception · doi:10.1177/0301006615599139 · Cited by 83
Liu, Y., Hu, B., Yan, W., & Zhi, L. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107716 · Cited by 96
Structure of subjective well-being among the elderly.
Stock, W. A., Okun, M. A., & Benin, M. H. (1986) · Psychology and Aging · doi:10.1037//0882-7974.1.2.91 · Cited by 107
A Bayesian framework for video affective representation
Soleymani, M., Kierkels, J. J. M., Chanel, G., & Pun, T. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349563 · Cited by 82
Cluster-Level Contrastive Learning for Emotion Recognition in Conversations
Yang, K., Zhang, T., Alhuzali, H., & Ananiadou, S. (2023) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2023.3243463 · Cited by 88
Multimodal Emotion Recognition Using Visual, Vocal and Physiological Signals: A Review
Udahemuka, G., Djouani, K., & Kurien, A. M. (2024) · Applied Sciences · doi:10.3390/app14178071 · Cited by 112
Judging Others' Emotions as a Function of the Others' Status
Conway, M. A., Fazio, R. D., & Mayman, S. (1999) · Social Psychology Quarterly · doi:10.2307/2695865 · Cited by 82
A theory of structured experience
Ellis, G. D., Freeman, P. A., Jamal, T. B., & Jiang, J. (2017) · Annals of Leisure Research · doi:10.1080/11745398.2017.1312468 · Cited by 89
Facial Expression Recognition: A Review of Trends and Techniques
Ekundayo, O., & Viriri, S. (2021) · IEEE Access · doi:10.1109/access.2021.3113464 · Cited by 92
Semi-supervised dimensional sentiment analysis with variational autoencoder
Wu, C., Wu, F., Wu, S., Yuan, Z., Liu, J., & Huang, Y. (2018) · Knowledge-Based Systems · doi:10.1016/j.knosys.2018.11.018 · Cited by 81
Mental representations of affect knowledge
Barrett, L. F., & Fossum, T. A. (2001) · Cognition & Emotion · doi:10.1080/0269993004200196 · Cited by 83
Hoey, J., Schröder, T., & Alhothali, A. (2013) · Artificial Intelligence · doi:10.1016/j.artint.2015.09.004 · Cited by 83
Individual Classification of Emotions Using EEG
Valenzi, S., Islam, T. T., Jurica, P., & Cichocki, A. S. (2014) · Journal of Biomedical Science and Engineering · doi:10.4236/jbise.2014.78061 · Cited by 85
Preferences for Individual Video Games as a Function of Their Emotional Effects on Players
Mehrabian, A., & Wixen, W. J. (1986) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1986.tb02274.x · Cited by 79
Self-citationJonauskaitė, D., Wicker, J. S., Möhr, C., Dael, N., Havelka, J., Παπαδάτου-Παστού, Μ., Zhang, M., & Oberfeld, D. (2019) · Royal Society Open Science · doi:10.1098/rsos.190741 · Cited by 77
A Review of Personality in Human‒Robot Interactions
Robert, L., Alahmad, R., Esterwood, C. T., Kim, S., You, S., & Zhang, Q. (2020) · Foundations and Trends® in Information Systems · doi:10.1561/2900000018 · Cited by 78
Yang, K., Kim, H. M., & Zimmerman, J. (2020) · Journal of Fashion Marketing and Management · doi:10.1108/jfmm-03-2019-0055 · Cited by 89
Hedonic Tone, Perceived Arousal, and Item Desirability: Three Components of Self-reported Mood
Barrett, L. F. (1996) · Cognition & Emotion · doi:10.1080/026999396380385 · Cited by 76
Affective Video Content Analysis: A Multidisciplinary Insight
Baveye, Y., Chamaret, C., Dellandréa, E., & Chen, L. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2661284 · Cited by 67
The minute-scale dynamics of online emotions reveal the effects of affect labeling
Fan, R., Varol, O., Varamesh, A., Barron, A. T. J., van de Leemput, I. A., Scheffer, M., & Bollen, J. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0490-5 · Cited by 97
Thome, J., Terpou, B. A., McKinnon, M. C., & Lanius, R. A. (2019) · Depression and Anxiety · doi:10.1002/da.22977 · Cited by 80
A Review of Different Approaches for Detecting Emotion from Text
Murthy, A. R., & Kumar, K. M. A. (2021) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/1110/1/012009 · Cited by 87
Mood Fluctuations: Women Versus Men and Menstrual Versus Other Cycles
McFarlane, J., Martin, C. L., & Williams, T. M. (1988) · Psychology of Women Quarterly · doi:10.1111/j.1471-6402.1988.tb00937.x · Cited by 93
Liu, T. Y., Chen, Y., Su, T.-P., Hsieh, J., & Chen, L. (2014) · BioMed Research International · doi:10.1155/2014/906104 · Cited by 76
Emotion Recognition From Gait Analyses: Current Research and Future Directions
Xu, S., Fang, J., Hu, X., Ngai, E. C. ‐., Wang, W. W., Guo, Y., & Leung, V. C. M. (2022) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3223251 · Cited by 88
Designing Effective Promotional Games: Opportunities and Problems
Ward, J. C., & Hill, R. P. (1991) · Journal of Advertising · doi:10.1080/00913367.1991.10673348 · Cited by 77
Scherer, K. R., Johnstone, & Klasmeyer, G. (2002) · Handbook of Affective Sciences · doi:10.1093/oso/9780195126013.003.0023 · Cited by 426
Restaurant hygiene attributes and consumers’ fear of COVID-19: Does psychological distress matter?
Siddiqi, U. I., Akhtar, N., & Islam, T. (2022) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2022.102972 · Cited by 74
Fitzgibbons, L. A., & Simons, R. F. (1992) · Psychophysiology · doi:10.1111/j.1469-8986.1992.tb02036.x · Cited by 73
Emotion detection for misinformation: A review
Liu, Z., Zhang, T., Yang, K., Thompson, P., Yu, Z., & Ananiadou, S. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102300 · Cited by 101
Schoefer, K., & Diamantopoulos, A. (2007) · Service Business · doi:10.1007/s11628-007-0024-0 · Cited by 73
The Four Dimensional Impact Of Color On Shoppers’ EmotionsPreprint
Brengman, M., & Geuens, M. (2003) · RePEc: Research Papers in Economics · Cited by 71
Vazquez, D., Dennis, C., & Zhang, Y. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.08.018 · Cited by 79
Novak, C. C., Lopa, J. L., & Novak, R. E. (2010) · Journal of Culinary Science & Technology · doi:10.1080/15428052.2010.535756 · Cited by 70
Affective Computing and the Impact of Gender and Age
Rukavina, S., Gruss, S., Hoffmann, H., Tan, J.-W., Walter, S., & Traue, H. C. (2016) · PLoS ONE · doi:10.1371/journal.pone.0150584 · Cited by 72
Sajjadi, P., Hoffmann, L., Cimiano, P., & Kopp, S. (2019) · Entertainment Computing · doi:10.1016/j.entcom.2019.100313 · Cited by 69
Impact of urban morphology on pedestrians: A review of urban approaches
Elzeni, M. M., elmokadem, A., & Badawy, N. M. (2022) · Cities · doi:10.1016/j.cities.2022.103840 · Cited by 69
Development of Computational Models of Emotions for Autonomous Agents: A Review
Rodríguez, L.-F., & Ramos, F. (2014) · Cognitive Computation · doi:10.1007/s12559-013-9244-x · Cited by 69
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Friman, M. (2010) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2010.04.006 · Cited by 69
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Soleymani, M., Chanel, G., Kierkels, J. J. M., & Pun, T. (2009) · International Journal of Semantic Computing · doi:10.1142/s1793351x09000744 · Cited by 69
Lee, D. G., Fels, D. I., & Udo, J. P. (2007) · Computers in entertainment · doi:10.1145/1279540.1279551 · Cited by 69
Emotion Recognition in Affective Tutoring Systems: Collection of Ground-truth Data
Petroviča, S., Anohina-Naumeca, A., & Ekenel, H. K. (2017) · Procedia Computer Science · doi:10.1016/j.procs.2017.01.157 · Cited by 69
A Mathematical Model Captures the Structure of Subjective Affect
Mattek, A. M., Wolford, G., & Whalen, P. J. (2017) · Perspectives on Psychological Science · doi:10.1177/1745691616685863 · Cited by 79
Semi-supervised Multi-modal Emotion Recognition with Cross-Modal Distribution Matching
Liang, J., Li, R., & Jin, Q. (2020) · Proceedings of the 28th ACM International Conference on Multimedia · doi:10.1145/3394171.3413579 · Cited by 73
Lighting in Digital Game Worlds: Effects on Affect and Play Performance
Knez, I., & Niedenthal, S. (2008) · CyberPsychology & Behavior · doi:10.1089/cpb.2007.0006 · Cited by 75
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Russell, J. A., & Steiger, J. H. (1982) · Journal of Research in Personality · doi:10.1016/0092-6566(82)90005-8 · Cited by 67
Self-citationMeasures of Individual Differences in Temperament
Mehrabian, A. (1978) · Educational and Psychological Measurement · doi:10.1177/001316447803800431 · Cited by 67
Self-citationThe Classification of Facial Expressions of Emotion: A Multidimensional-Scaling Approach
Katsikitis, M. (1997) · Perception · doi:10.1068/p260613 · Cited by 70
The Structure of Emotions: Canada-United States Comparisons
MacKinnon, N. J., & Keating, L. J. (1989) · Social Psychology Quarterly · doi:10.2307/2786905 · Cited by 66
Extraversion, neuroticism, psychoticism and recreational choice
Kirkcaldy, B. D., & Furnham, A. F. (1991) · Personality and Individual Differences · doi:10.1016/0191-8869(91)90229-5 · Cited by 66
A Connotative Space for Supporting Movie Affective Recommendation
Benini, S., Canini, L., & Leonardi, R. (2011) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2011.2163058 · Cited by 66
The immutability of valence and arousal in the foundation of emotion.
Bliss‐Moreau, E., Williams, L. A., & Santistevan, A. C. (2019) · Emotion · doi:10.1037/emo0000606 · Cited by 71
Combining Facial and Postural Expressions of Emotions in a Virtual Character
Clavel, C., Plessier, J., Martin, J., Ach, L., & Morel, B. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04380-2_31 · Cited by 64
Nijboer, F., Morin, F. O., Carmien, S. P., Koene, R. A., Leon, E., & Hoffmann, U. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349479 · Cited by 65
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Loureiro, S. M. C., & Sarmento, E. M. (2018) · International Journal of Bank Marketing · doi:10.1108/ijbm-03-2017-0061 · Cited by 67
Mapping a multidimensional emotion in response to television commercials
Morris, J. D., Klahr, N. J., Shen, F., Villegas, J., Wright, P. K., He, G., & Liu, Y. (2008) · Human Brain Mapping · doi:10.1002/hbm.20544 · Cited by 63
Priming semantic concepts affects the dynamics of aesthetic appreciation
Faerber, S. J., Leder, H., Gerger, G., & Carbon, C. (2010) · Acta Psychologica · doi:10.1016/j.actpsy.2010.06.006 · Cited by 64
Moore, G. T., & Sugiyama, T. (2007) · Children Youth and Environments · doi:10.1353/cye.2007.0023 · Cited by 72
Metadata
- 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
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- arousal, emotional state, acquiescence bias, semantic differential, definition of emotion
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