Recognizing emotions on the basis of keystroke dynamics
Abstract
The article describes a research on recognizing emotional states on the basis of keystroke dynamics. An overview of various studies and applications of emotion recognition based on data coming from keyboard is presented. Then, the idea of an experiment is presented, i.e. the way of collecting and labeling training data, extracting features and finally training classifiers. Different classification approaches are proposed to be tested: universal vs. individual models, multiclass vs. two-class. The obtained results reveal which of these approaches are appropriate for the given task. The individual two-class models turn out to be the most accurate.
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Keystroke Dynamics can be used to determine the authors' emotional state.
“Besides its natural use for authentication, KD can also be used to determine the authors' emotional state [102][103][104][105]”
From Online grooming detection: A comprehensive survey of child exploitation in chat logs (2023) · cites this paper as [104]
Cites
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 · cited 1× · see citing works
“However, they may also deliver valuable information, especially when analyzed together with other affect information [1], [2].”
BackgroundIdentifying emotional states using keystroke dynamics
Epp, C., Lippold, M., & Mandryk, R. L. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979046 · Cited by 364 · see citing works
Affect Recognition from Face and Body: Early Fusion vs. Late Fusion
Gunes, H., & Piccardi, M. (2006) · 2005 IEEE International Conference on Systems, Man and Cybernetics · doi:10.1109/icsmc.2005.1571679 · Cited by 191 · see citing works
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Online grooming detection: A comprehensive survey of child exploitation in chat logs
Borj, P. R., Raja, K., & Bours, P. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.110039 · Cited by 38 · see citing works
- Authors
- Kolakowska, A.
- Venue
- 2015 8th International Conference on Human System Interaction (HSI)
- Publisher
- IEEE
- Published
- 2015-06
- Pages
- 291-297
- OpenAlex
- W1575225931
- Cited by
- 30
- References
- 3
- Citations by year
- 2025: 2 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 4 · 2020: 4 · 2019: 4 · 2018: 1 · 2017: 3 · 2016: 5
- FWCI
- 4.01
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Conference on Human System Interactions (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- emotion recognition, keystroke dynamics, individual model, multi-class classification, binary classification, feature extraction, training data collection, classifier comparison
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