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Emotion Analysis for Personality Inference from EEG Signals
Zhao, Guozhen1; Ge, Yan1; Shen, Biying1; Wei, Xingjie2; Wang, Hao3
First AuthorGuozhen Zhao
2018-07-01
Source PublicationIEEE TRANSACTIONS ON AFFECTIVE COMPUTING
Correspondent Emailzhaogz@psych.ac.cn ; gey@psych.ac.cn ; shenby@psych.ac.cn
ISSN1949-3045
Volume9Issue:3Pages:362-371
Abstract

The stable relationship between personality and EEG ensures the feasibility of personality inference from brain activities. In this paper, we recognize an individual's personality traits by analyzing brain waves when he or she watches emotional materials. Thirty-seven participants took part in this study and watched 7 standardized film clips that characterize real-life emotional experiences and target seven discrete emotions. Features extracted from EEG signals and subjective ratings enter the SVM classifier as inputs to predict five dimensions of personality traits. Our model achieves better classification performance for Extraversion (81.08 percent), Agreeableness (86.11 percent), and Conscientiousness (80.56 percent) when positive emotions are elicited than negative ones, higher classification accuracies for Neuroticism (78.38-81.08 percent) when negative emotions, except disgust, are evoked than positive emotions, and the highest classification accuracy for Openness (83.78 percent) when a disgusting film clip is presented. Additionally, the introduction of features from subjective ratings increases not only classification accuracy in all five personality traits (ranging from 0.43 percent for Conscientiousness to 6.3 percent for Neuroticism) but also the discriminative power of the classification accuracies between five personality traits in each category of emotion. These results demonstrate the advantage of personality inference from EEG signals over state-of-the-art explicit behavioral indicators in terms of classification accuracy.

KeywordEmotion Analysis Emotion Regulation Personality Inference Eeg Big-five Personality Affective Computing
DOI10.1109/TAFFC.2017.2786207
Language英语
Funding OrganizationNational Key Research and Development Plan ; National Natural Science Foundation of China
Funding ProjectNational Key Research and Development Plan[2016YFB1001200] ; National Key Research and Development Plan[2017YFB0802800] ; National Natural Science Foundation of China[31771226] ; National Natural Science Foundation of China[61672501]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000443893400007
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS KeywordEvent-related Synchronization ; Individual-differences ; Extroversion-introversion ; Motivational Direction ; Discriminant-analysis ; 5-factor Model ; Traits ; Anger ; Neuroticism ; Performance
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/26958
Collection中国科学院行为科学重点实验室
Corresponding AuthorZhao, Guozhen; Ge, Yan
Affiliation1.Inst Psychol, CAS Key Laboratonj Behav Sci, Beijing 100101, Peoples R China
2.Univ Bath, Sch Management, Bath BA2 7AY, Avon, England
3.Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Guozhen,Ge, Yan,Shen, Biying,et al. Emotion Analysis for Personality Inference from EEG Signals[J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,2018,9(3):362-371.
APA Zhao, Guozhen,Ge, Yan,Shen, Biying,Wei, Xingjie,&Wang, Hao.(2018).Emotion Analysis for Personality Inference from EEG Signals.IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,9(3),362-371.
MLA Zhao, Guozhen,et al."Emotion Analysis for Personality Inference from EEG Signals".IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 9.3(2018):362-371.
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