Affective Computing
Open accessAbstract
According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more—that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
EDA and EKG sensors have been shown to be reliable for emotion detection.
“In contrast, the goal of our system was to use on-body sensors with EDA and electrocardiogram (EKG), since these sensors have been shown to be reliable for emotion detection [14,17,18].”
From Food and Mood: Just-in-Time Support for Emotional Eating (2013) · cites this paper as [18]
Cited by
Sorted by citations
Opinion Mining and Sentiment Analysis
Pang, B., & Lee, L. (2008) · now publishers, Inc. eBooks · doi:10.1561/9781601981516 · Cited by 6,957 · see citing works
Statistical pattern recognition: a review
Jain, A. K., Duin, P., & Mao, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.824819 · Cited by 6,795 · see citing works
DEAP: A Database for Emotion Analysis ;Using Physiological Signals
Koelstra, S., Muhl, C., Soleymani, M., Lee, J.-S., Yazdani, A., Ebrahimi, T., Pun, T., Nijholt, A., & Patras, I. (2012) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.15 · Cited by 5,093 · see citing works
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · see citing works
IEMOCAP: Interactive emotional dyadic motion capture database
Busso, C., Bulut, M., Lee, C.-C., Kazemzadeh, A., Mower, E., Kim, S., Chang, J. N., Lee, S., & Narayanan, S. S. (2008) · Language Resources and Evaluation · doi:10.1007/s10579-008-9076-6 · Cited by 3,869 · see citing works
Artificial intelligence in service
Huang, M.-H., & Rust, R. T. (2018) · Journal of Service Research · doi:10.1177/1094670517752459 · Cited by 3,978 · see citing works
Trust in Automation: Designing for Appropriate Reliance
Lee, J. D., & See, K. A. (2004) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.1.50_30392 · Cited by 6,605 · see citing works
(2006) · doi:10.1080/01449290500330331 · Cited by 3,026 · see citing works
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797 · see citing works
TARGET ARTICLES: "Emotional Intelligence: Theory, Findings, and Implications"
Mayer, J. D., Salovey, P., & Caruso, D. R. (2004) · Psychological Inquiry · doi:10.1207/s15327965pli1503_02 · Cited by 2,550 · see citing works
Toward machine emotional intelligence: analysis of affective physiological state
Picard, R. W., Vyzas, E., & Healey, J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.954607 · Cited by 2,334 · see citing works
Self-citation(2006) · Cited by 2,256 · see citing works
Human abilities: emotional intelligence
Mayer, J. D., Roberts, R. D., & Barsade, S. G. (2008) · Annual Review of Psychology · doi:10.1146/annurev.psych.59.103006.093646 · Cited by 2,170 · see citing works
Vocal communication of emotion: A review of research paradigms
Scherer, K. (2003) · Speech Communication · doi:10.1016/s0167-6393(02)00084-5 · Cited by 2,044 · see citing works
Content-based Recommender Systems: State of the Art and Trends
Lops, P., de Gemmis, M., & Semeraro, G. M. (2010) · Springer eBooks · doi:10.1007/978-0-387-85820-3_3 · Cited by 1,941 · see citing works
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
Calvo, R. A., & D'Mello, S. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.1 · Cited by 1,893 · see citing works
Communication of emotions in vocal expression and music performance: Different channels, same code?
Juslin, P. N., & Laukka, P. (2003) · Psychological Bulletin · doi:10.1037/0033-2909.129.5.770 · Cited by 1,826 · see citing works
The Adaptive Markets Hypothesis
Lo, A. W. (2004) · The Journal of Portfolio Management · doi:10.3905/jpm.2004.442611 · Cited by 1,711 · see citing works
Human–Robot Interaction: A Survey
Goodrich, M. A., & Schultz, A. C. (2008) · Foundations and Trends® in Human–Computer Interaction · doi:10.1561/1100000005 · Cited by 1,541 · see citing works
Content-based multimedia information retrieval: State of the art and challenges
Lew, M. S., Sebe, N., Djeraba, C., & Jain, R. (2006) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/1126004.1126005 · Cited by 1,528 · see citing works
Charting past, present, and future research in ubiquitous computing
Abowd, G. D., & Mynatt, E. D. (2000) · ACM Transactions on Computer-Human Interaction · doi:10.1145/344949.344988 · Cited by 1,462 · see citing works
What is user engagement? A conceptual framework for defining user engagement with technology
O'Brien, H. L., & Toms, E. G. (2008) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20801 · Cited by 1,397 · see citing works
Establishing and maintaining long-term human-computer relationships
Bickmore, T. W., & Picard, R. W. (2005) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1067860.1067867 · Cited by 1,333 · see citing works
Self-citationAffective Computing and Sentiment Analysis
Cambria, E. (2016) · IEEE Intelligent Systems · doi:10.1109/mis.2016.31 · Cited by 1,445 · see citing works
EmotionMeter: A Multimodal Framework for Recognizing Human Emotions
Zheng, W.-L., Liu, W., Lu, Y., Lu, B.-L., & Cichocki, A. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2797176 · Cited by 1,276 · see citing works
Emotions Recognition Using EEG Signals: A Survey
Alarcao, S. M., & Fonseca, M. J. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2714671 · Cited by 1,201 · see citing works
Speech Recognition Using Deep Neural Networks: A Systematic Review
Nassif, A. B., Shahin, I. M. A., Attili, I. B., Azzeh, M., & Shaalan, K. F. (2019) · IEEE Access · doi:10.1109/access.2019.2896880 · Cited by 1,159 · see citing works
Embodied Cognition: A field guide
Anderson, M. L. (2003) · Artificial Intelligence · doi:10.1016/s0004-3702(03)00054-7 · Cited by 1,129 · see citing works
Affective interactions using virtual reality: the link between presence and emotions
Riva, G., Mantovani, F., Capideville, C. S., Preziosa, A., Morganti, F., Villani, D., Gaggioli, A., Botella, C., & Alcañiz, M. (2007) · CyberPsychology & Behavior · doi:10.1089/cpb.2006.9993 · Cited by 1,111 · see citing works
Human-Robot Interaction: A Survey
Goodrich, M. A., & Schultz, A. C. (2007) · now publishers, Inc. eBooks · doi:10.1561/9781601980939 · Cited by 1,104 · see citing works
Cooperstock, J. R. (2009) · Wiley eBooks · doi:10.1002/9780470050118.ecse524 · Cited by 1,084 · see citing works
Framework of product experience
Desmet, P., & Hekkert, P. (2007) · Research Repository (Delft University of Technology) · Cited by 1,034 · see citing works
Providing architectural support for building context-aware applications
Dey, A. K., & Abowd, G. D. (2000) · UPT. Syiah Kuala University Library (Syiah Kuala University) · Cited by 1,034 · see citing works
Attention web designers: You have 50 milliseconds to make a good first impression!
Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. M. (2006) · Behaviour and Information Technology · doi:10.1080/01449290500330448 · Cited by 1,025 · see citing works
User Models for Adaptive Hypermedia and Adaptive Educational Systems
Brusilovsky, P. L., & Millán, E. (2007) · Springer eBooks · doi:10.1007/978-3-540-72079-9_1 · Cited by 994 · see citing works
Affective computing: challenges
Picard, R. W. (2003) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(03)00052-1 · Cited by 978 · see citing works
Self-citationMultimodal human–computer interaction: A survey
Jaimes, A., & Sebe, N. (2007) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2006.10.019 · Cited by 965 · see citing works
Emotion recognition system using short-term monitoring of physiological signals
Kim, K. H., Bang, S. W., & Kim, S. R. (2004) · Medical & Biological Engineering & Computing · doi:10.1007/bf02344719 · Cited by 944 · see citing works
Sengers, P., Boehner, K., David, S., & Kaye, J. '. (2005) · Proceedings of the 4th decennial conference on Critical computing: between sense and sensibility · doi:10.1145/1094562.1094569 · Cited by 747 · see citing works
Baker, R. S. J. D., D'Mello, S. K., Rodrigo, M. M. T., & Graesser, A. C. (2010) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2009.12.003 · Cited by 936 · see citing works
Sentiment analysis in multiple languages
Abbasi, A., Chen, H., & Salem, A. (2008) · ACM Transactions on Information Systems · doi:10.1145/1361684.1361685 · Cited by 892 · see citing works
GoEmotions: A Dataset of Fine-Grained Emotions
Demszky, D., Movshovitz-Attias, D., Ko, J., Cowen, A., Nemade, G., & Ravi, S. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.372 · Cited by 873 · see citing works
Pupil size variation as an indication of affective processing
Partala, T., & Surakka, V. (2003) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(03)00017-x · Cited by 836 · see citing works
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
Zhang, J., Yin, Z., Chen, P., & Nichele, S. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.01.011 · Cited by 806 · see citing works
Converging Technologies for Improving Human Performance
Roco, M. C., & Bainbridge, W. S. (2003) · Springer eBooks · doi:10.1007/978-94-017-0359-8 · Cited by 792 · see citing works
Toward an affect-sensitive multimodal human-computer interaction
Pantic, M., & Rothkrantz, L. J. M. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.817122 · Cited by 791 · see citing works
Alm, C. O., Roth, D., & Sproat, R. (2005) · doi:10.3115/1220575.1220648 · Cited by 781 · see citing works
The design and implementation of Xiaoice, an empathetic social chatbot
Zhou, L., Gao, J., Li, D., & Shum, H.-Y. (2020) · Computational Linguistics · doi:10.1162/coli_a_00368 · Cited by 777 · see citing works
(2002) · Cited by 770 · see citing works
Emotional state classification from EEG data using machine learning approach
Wang, X.-W., Nie, D., & Lu, B.-L. (2014) · Neurocomputing · doi:10.1016/j.neucom.2013.06.046 · Cited by 755 · see citing works
Kort, B. W., Reilly, R., & Picard, R. W. (2002) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2001.943850 · Cited by 751 · see citing works
Self-citationAutoTutor: an intelligent tutoring system with mixed-initiative dialogue.
Graesser, A. C., Chipman, P., Haynes, B. C., & Olney, A. (2005) · IEEE Transactions on Education · doi:10.1109/te.2005.856149 · Cited by 750 · see citing works
Foundations for a new science of learning
Meltzoff, A. N., Kuhl, P. K., Movellan, J., & Sejnowski, T. J. (2009) · Science · doi:10.1126/science.1175626 · Cited by 723 · see citing works
Building Intelligent Interactive Tutors : student-centered strategies for revolutionizing e-learning
Woolf, B. P. (2009) · HAL · Cited by 716 · see citing works
Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments
Johnson, W. L., Rickel, J. W., & Lester, J. C. (2000) · Cited by 711 · see citing works
A Spontaneous Micro-expression Database: Inducement, collection and baseline
Li, X., Pfister, T., Huang, X., Zhao, G., & Pietikäinen, M. (2013) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2013.6553717 · Cited by 703 · see citing works
Review: Multi-objective optimization methods and application in energy saving
Cui, Y., Geng, Z., Zhu, Q., & Han, Y. M. (2017) · Energy · doi:10.1016/j.energy.2017.02.174 · Cited by 688 · see citing works
Emotion Recognition From EEG Using Higher Order Crossings
Petrantonakis, P. C., & Hadjileontiadis, L. J. (2009) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2009.2034649 · Cited by 687 · see citing works
Learning to identify emotions in text
Strapparava, C., & Mihalcea, R. F. (2008) · ACM Symposium on Applied Computing · doi:10.1145/1363686.1364052 · Cited by 673 · see citing works
Definition and synergies of cognitive infocommunications
Bárányi, P., & Csapó, Á. (2012) · SZTAKI Publication Repository (Hungarian Academy of Sciences) · Cited by 662 · see citing works
Emotional design in multimedia learning.
Um, E. R., Plass, J. L., Hayward, E. O., & Homer, B. D. (2011) · Journal of Educational Psychology · doi:10.1037/a0026609 · Cited by 670 · see citing works
Speech Emotion Recognition Using Deep Learning Techniques: A Review
Khalil, R. A., Jones, E., Babar, M. I., Jan, T., Zafar, M. H., & Alhussain, T. (2019) · IEEE Access · doi:10.1109/access.2019.2936124 · Cited by 702 · see citing works
Feminist Visualization: Re-envisioning GIS as a Method in Feminist Geographic Research
Kwan, M. (2002) · Annals of the Association of American Geographers · doi:10.1111/1467-8306.00309 · Cited by 635 · see citing works
Methods for Evaluating Interactive Information Retrieval Systems with Users
Kelly, D. (2009) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000012 · Cited by 638 · see citing works
A Review and Meta-Analysis of Multimodal Affect Detection Systems
D’Mello, S. K., & Kory-Westlund, J. M. (2015) · ACM Computing Surveys · doi:10.1145/2682899 · Cited by 654 · see citing works
Affect and learning: An exploratory look into the role of affect in learning with AutoTutor
Craig, S., Graesser, A., Sullins, J., & Gholson, B. (2004) · Journal of Educational Media · doi:10.1080/1358165042000283101 · Cited by 630 · see citing works
Usability, aesthetics and emotions in human–technology interaction
Thüring, M., & Mahlke, S. (2007) · International Journal of Psychology · doi:10.1080/00207590701396674 · Cited by 624 · see citing works
Virtual reality and mixed reality for virtual learning environments
Pan, Z., Cheok, A. D., Yang, H., Zhu, J., & Shi, J. (2005) · Computers & Graphics · doi:10.1016/j.cag.2005.10.004 · Cited by 611 · see citing works
Fundamentals of physiological computing
Fairclough, S. H. (2009) · Interacting with Computers · doi:10.1016/j.intcom.2008.10.011 · Cited by 608 · see citing works
Affective video content representation and modeling
Hanjalić, A., & Xu, L.-Q. (2005) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2004.840618 · Cited by 593 · see citing works
Staying open to interpretation
Sengers, P., & Gaver, B. (2006) · Proceedings of the 6th conference on Designing Interactive systems · doi:10.1145/1142405.1142422 · Cited by 592 · see citing works
Automatic prediction of frustration
Kapoor, A., Burleson, W., & Picard, R. W. (2007) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2007.02.003 · Cited by 592 · see citing works
Self-citationEEG-Based Emotion Recognition via Channel-Wise Attention and Self Attention
Tao, W., Li, C., Song, R., Cheng, J., Liu, Y., Wan, F., & Chen, X. (2020) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2020.3025777 · Cited by 590 · see citing works
Cognitive Infocommunications (CogInfoCom)
Bárányi, P., Csapó, Á., & Sallai, G. (2015) · Springer eBooks · doi:10.1007/978-3-319-19608-4 · Cited by 586 · see citing works
Can Large Language Models Transform Computational Social Science?
Ziems, C., Held, W., Shaikh, O., Chen, J., Zhang, Z., & Yang, D. (2024) · Computational Linguistics · doi:10.1162/coli_a_00502 · Cited by 585 · see citing works
Valstar, M., Schuller, B. W., Smith, K., Eyben, F., Jiang, B., Bilakhia, S., Schnieder, S., Cowie, R., & Pantić, M. (2013) · doi:10.1145/2512530.2512533 · Cited by 581 · see citing works
The urban brain: Analysing outdoor physical activity with mobile EEG
Aspinall, P., Mavros, P., Coyne, R., & Roe, J. (2015) · British Journal of Sports Medicine · doi:10.1136/bjsports-2012-091877 · Cited by 574 · see citing works
A Review of Human Activity Recognition Methods
Vrigkas, M., Nikou, C., & Kakadiaris, I. A. (2015) · Frontiers in Robotics and AI · doi:10.3389/frobt.2015.00028 · Cited by 571 · see citing works
AutoTutor: A tutor with dialogue in natural language
Graesser, A. C., Lu, S., Jackson, G. T., Mitchell, H. H., Ventura, M., Olney, A. M., & Louwerse, M. M. (2004) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03195563 · Cited by 567 · see citing works
Aura: An Architectural Framework for User Mobility in Ubiquitous Computing Environments
Sousa, J. P., & Garlan, D. (2002) · IFIP advances in information and communication technology · doi:10.1007/978-0-387-35607-5_2 · Cited by 551 · see citing works
ON THE NATURE AND DEVELOPMENT OF SOCIAL PRESENCE IN ONLINE COURSE DISCUSSIONS
Swan, K. P., & Shih, L. F. (2005) · Online Learning · doi:10.24059/olj.v9i3.1788 · Cited by 550 · see citing works
Schuller, B. W. (2018) · Communications of the ACM · doi:10.1145/3129340 · Cited by 547 · see citing works
Kamil, A. C. (2001) · Evolution and Human Behavior · doi:10.1016/s1090-5138(01)00068-x · Cited by 548 · see citing works
Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis
Lo, A. W. (2005) · Cited by 542 · see citing works
Mandryk, R. L., & Atkins, M. S. (2007) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.11.011 · Cited by 538 · see citing works
A model of textual affect sensing using real-world knowledge
Liu, H., Lieberman, H. A., & Selker, T. (2003) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/604045.604067 · Cited by 533 · see citing works
Learner motivation and E-learning design: A multinationally validated process
Keller, J. M., & Suzuki, K. (2004) · Journal of Educational Television · doi:10.1080/1358165042000283084 · Cited by 523 · see citing works
Nass, C., & Lee, K. M. (2001) · Journal of Experimental Psychology: Applied · doi:10.1037/1076-898x.7.3.171 · Cited by 522 · see citing works
Automatic mood detection and tracking of music audio signals
Lu, L., Liu, D., & Zhang, H.-J. (2005) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tsa.2005.860344 · Cited by 518 · see citing works
Using psychophysiological techniques to measure user experience with entertainment technologies
Mandryk, R. L., Inkpen, K. M., & Calvert, T. W. (2006) · Behaviour and Information Technology · doi:10.1080/01449290500331156 · Cited by 516 · see citing works
Socially Situated Cognition: Cognition in its Social Context
Smith, E. R., & Semin, G. R. (2004) · Advances in experimental social psychology · doi:10.1016/s0065-2601(04)36002-8 · Cited by 517 · see citing works
Towards a feminist HCI methodology
Bardzell, S., & Bardzell, J. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979041 · Cited by 513 · see citing works
Brave, S., Nass, C., & Hutchinson, K. (2005) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2004.11.002 · Cited by 512 · see citing works
Tao, J., & Tan, T. (2005) · Lecture notes in computer science · doi:10.1007/11573548_125 · Cited by 511 · see citing works
Affective Learning — A Manifesto
Picard, R. W., Papert, S. A., Bender, W. R., Blumberg, B. M., Breazeal, C., Cavallo, D. P., Machover, T., Resnick, M., Roy, D. K., & Strohecker, C. (2004) · BT Technology Journal · doi:10.1023/b:bttj.0000047603.37042.33 · Cited by 511 · see citing works
Self-citationEEG Based Emotion Recognition: A Tutorial and Review
Li, X., Zhang, Y., Tiwari, P., Song, D., Hu, B., Yang, M., Zhao, Z., Kumar, N., & Marttinen, P. (2023) · ACM Computing Surveys · doi:10.1145/3524499 · Cited by 508 · see citing works
Probabilistic assessment of user's emotions in educational games
Conati, C. (2002) · Applied Artificial Intelligence · doi:10.1080/08839510290030390 · Cited by 498 · see citing works
Cardiovascular, electrodermal, and respiratory response patterns to fear‐ and sadness‐inducing films
Kreibig, S. D., Wilhelm, F. H., Roth, W. T., & Gross, J. J. (2007) · Psychophysiology · doi:10.1111/j.1469-8986.2007.00550.x · Cited by 495 · see citing works
Stress detection in daily life scenarios using smart phones and wearable sensors: A survey
Can, Y. S., Arnrich, B., & Ersoy, C. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103139 · Cited by 439 · see citing works
Survey on Emotional Body Gesture Recognition
Noroozi, F., Corneanu, C. A., Kamińska, D., Sapiński, T., Escalera, S., & Anbarjafari, G. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2874986 · Cited by 491 · see citing works
- Authors
- Picard, R. W.
- Affiliations
- MIT Media Lab (US)
- Corresponding author
- Picard, Rosalind W.
- ORCID
- Picard, Rosalind W.
- Venue
- MIT Press
- Publisher
- The MIT Press
- Published
- 1997-09-24
- OpenAlex
- W2339343773
- Cited by
- 7,382
- References
- 0
- Citations by year
- 2026: 376 · 2025: 295 · 2024: 212 · 2023: 266 · 2022: 208 · 2021: 274 · 2020: 322 · 2019: 356 · 2018: 283 · 2017: 279 · 2016: 301 · 2015: 318 · 2014: 315 · 2013: 335 · 2012: 329
- FWCI
- 92.96
- Type
- book
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-sa
- Locations
- The MIT Press eBooks (publishedVersion)
- PsycEXTRA Dataset (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Keywords
- affective computing, emotion recognition, emotion models, emotion synthesis, wearable computers, human-computer interaction, decision-making, pattern recognition
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review