research-article

No Need to Laugh Out Loud: Predicting Humor Appraisal of Comic Strips Based on Physiological Signals in a Realistic Environment

Authors:

Giulio JacucciAuthors Info & Claims

ACM Transactions on Computer-Human Interaction (TOCHI), Volume 24, Issue 6

Article No.: 40, Pages 1 - 29

https://doi.org/10.1145/3157730

Published: 19 December 2017 Publication History

Abstract

We explore electroencephalography (EEG), electrodermal activity (EDA), and electrocardiography (ECG) as valid sources to infer humor appraisal in a realistic environment. We report on an experiment in which 25 participants browsed a popular user-generated humorous content website while their physiological responses were recorded. We build predictive models to infer the participants’ appraisal of the humorousness of the content and demonstrate that the fusion of several physiological signals can lead to classification performances up to 0.73 in terms of the area under the ROC curve (AUC). We identify that the most discriminative changes in physiological signals happen at the later stages of the information consumption process, reflected in changes on the upper EEG frequency bands, higher levels of EDA, and heart-rate acceleration. Additionally, we present a comprehensive analysis by benchmarking the predictive power of each of the physiological signals separately, and by comparing them to state-of-the-art facial recognition algorithms based on facial video recordings. The classification performance ranges from 0.88 (in terms of AUC) when combining physiological signals and video recordings, to 0.55 when using ECG signals alone.

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Index Terms

No Need to Laugh Out Loud: Predicting Humor Appraisal of Comic Strips Based on Physiological Signals in a Realistic Environment
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Transactions on Computer-Human Interaction

ACM Transactions on Computer-Human Interaction Volume 24, Issue 6

December 2017

162 pages

ISSN:1073-0516

EISSN:1557-7325

DOI:10.1145/3175498

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Publication History

Published: 19 December 2017

Accepted: 01 October 2017

Revised: 01 October 2017

Received: 01 June 2017

Published in TOCHI Volume 24, Issue 6

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Banik SKumar HGanapathy NSwaminathan R(2024)Exploring Central-Peripheral Nervous System Interaction Through Multimodal Biosignals: A Systematic ReviewIEEE Access10.1109/ACCESS.2024.339403612(60347-60368)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3394036
Liu ZCourant RKalogeiton V(2024)FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the WildInternational Journal of Computer Vision10.1007/s11263-024-02000-2132:8(2885-2906)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s11263-024-02000-2
Stangl FRiedl R(2024)Neurophysiological Measurements in the Research Field of Interruption Science: Insights into Applied Methods for Different Interruption Types Based on an Umbrella ReviewInformation Systems and Neuroscience10.1007/978-3-031-58396-4_11(123-152)Online publication date: 26-Jul-2024
https://doi.org/10.1007/978-3-031-58396-4_11
Zargham NReicherts LAvanesi VRogers YMalaka R(2023)Tickling Proactivity: Exploring the Use of Humor in Proactive Voice AssistantsProceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia10.1145/3626705.3627777(294-320)Online publication date: 3-Dec-2023
https://dl.acm.org/doi/10.1145/3626705.3627777
Zargham NAvanesi VReicherts LScott ARogers YMalaka R(2023)“Funny How?” A Serious Look at Humor in Conversational AgentsProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3603761(1-7)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3603761
Ruiz‐Padial EMoreno‐Padilla MReyes del Paso G(2023)Did you get the joke? Physiological, subjective and behavioral responses to mirthPsychophysiology10.1111/psyp.1429260:6Online publication date: 20-Mar-2023
https://doi.org/10.1111/psyp.14292
Yang KTag BWang CGu YSarsenbayeva ZDingler TWadley GGoncalves J(2023)Survey on Emotion Sensing Using Mobile DevicesIEEE Transactions on Affective Computing10.1109/TAFFC.2022.322048414:4(2678-2696)Online publication date: 1-Oct-2023
https://doi.org/10.1109/TAFFC.2022.3220484
Liu ZCourant RKalogeiton V(2023)FunnyNet: Audiovisual Learning of Funny Moments in VideosComputer Vision – ACCV 202210.1007/978-3-031-26316-3_26(433-450)Online publication date: 2-Mar-2023
https://doi.org/10.1007/978-3-031-26316-3_26
Putze FPutze SSagehorn MMicek CSolovey E(2022)Understanding HCI Practices and Challenges of Experiment Reporting with Brain Signals: Towards Reproducibility and ReuseACM Transactions on Computer-Human Interaction10.1145/349055429:4(1-43)Online publication date: 31-Mar-2022
https://dl.acm.org/doi/10.1145/3490554
Stangl FRiedl R(2022)Measurement of Heart Rate and Heart Rate Variability in NeuroIS Research: Review of Empirical ResultsInformation Systems and Neuroscience10.1007/978-3-031-13064-9_29(285-299)Online publication date: 3-Dec-2022
https://doi.org/10.1007/978-3-031-13064-9_29
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