research-article

Identifying emotional states using keystroke dynamics

Authors:

Michael Lippold,

Regan L. MandrykAuthors Info & Claims

CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 715 - 724

https://doi.org/10.1145/1978942.1979046

Published: 07 May 2011 Publication History

Abstract

The ability to recognize emotions is an important part of building intelligent computers. Emotionally-aware systems would have a rich context from which to make appropriate decisions about how to interact with the user or adapt their system response. There are two main problems with current system approaches for identifying emotions that limit their applicability: they can be invasive and can require costly equipment. Our solution is to determine user emotion by analyzing the rhythm of their typing patterns on a standard keyboard. We conducted a field study where we collected participants' keystrokes and their emotional states via self-reports. From this data, we extracted keystroke features, and created classifiers for 15 emotional states. Our top results include 2-level classifiers for confidence, hesitance, nervousness, relaxation, sadness, and tiredness with accuracies ranging from 77 to 88%. In addition, we show promise for anger and excitement, with accuracies of 84%.

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https://dl.acm.org/doi/10.1145/3677080
Cockburn AHills DChen ZGutwin C(2024)User Interface Evaluation Through Implicit-Association TestsProceedings of the ACM on Human-Computer Interaction10.1145/36646368:EICS(1-23)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3664636
Sim KFortuno KChoo K(2024)Towards Understanding Emotions for Engaged Mental Health ConversationsCompanion Publication of the 2024 ACM Designing Interactive Systems Conference10.1145/3656156.3663694(176-180)Online publication date: 1-Jul-2024
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Index Terms

Identifying emotional states using keystroke dynamics
1. Computing methodologies
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices

Index terms have been assigned to the content through auto-classification.

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Information

Published In

cover image ACM Conferences

CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

May 2011

3530 pages

ISBN:9781450302289

DOI:10.1145/1978942

General Chair:
Desney Tan
Microsoft Research
,
Program Chairs:
Geraldine Fitzpatrick
Vienna University of Technology
,
Carl Gutwin
University of Saskatchewan
,
Bo Begole
PARC
,
Wendy A. Kellogg
IBM Research

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 07 May 2011

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CHI '11

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CHI '11: CHI Conference on Human Factors in Computing Systems

May 7 - 12, 2011

BC, Vancouver, Canada

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CHI '11 Paper Acceptance Rate 410 of 1,532 submissions, 27%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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CHI '25

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CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

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Wijkstra MRogers KMandryk RVeltkamp RFrommel J(2024)How To Tame a Toxic Player? A Systematic Literature Review on Intervention Systems for Toxic Behaviors in Online Video GamesProceedings of the ACM on Human-Computer Interaction10.1145/36770808:CHI PLAY(1-32)Online publication date: 15-Oct-2024
https://dl.acm.org/doi/10.1145/3677080
Cockburn AHills DChen ZGutwin C(2024)User Interface Evaluation Through Implicit-Association TestsProceedings of the ACM on Human-Computer Interaction10.1145/36646368:EICS(1-23)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3664636
Sim KFortuno KChoo K(2024)Towards Understanding Emotions for Engaged Mental Health ConversationsCompanion Publication of the 2024 ACM Designing Interactive Systems Conference10.1145/3656156.3663694(176-180)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3656156.3663694
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Ma D(2024)Assessment of Human State Based on Data from Keyboard Activity2024 V International Conference on Neural Networks and Neurotechnologies (NeuroNT)10.1109/NeuroNT62606.2024.10585372(6-10)Online publication date: 20-Jun-2024
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Boldi ARapp ABirk M(2024)Stress in Esports: A Qualitative Study on The Interplay of Player Experiences and Organizational SystemsInternational Journal of Human–Computer Interaction10.1080/10447318.2024.2423343(1-24)Online publication date: 11-Nov-2024
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Gopalakrishnan AGururajan RZhou XVenkataraman RChan KHiggins N(2024)A survey of autonomous monitoring systems in mental healthWIREs Data Mining and Knowledge Discovery10.1002/widm.152714:3Online publication date: 24-Jan-2024
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Piet JSharma APaxson VWagner DCalandrino JTroncoso C(2023)Network detection of interactive SSH impostors using deep learningProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620477(4283-4300)Online publication date: 9-Aug-2023
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