• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.03a
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• pp.11-15
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• 1999

The discrete state theory on emotion postulated that there existed discrete emotions, such as happiness, anger, fear, disgust, and so forth. Many investigators who emphasized discreteness of emotions have suggested that discrete emotions entailed their specific activities in the autonomic nervous system. The purposes of this study were to develop a model of emotion-specific physiological response patterns. The study postulated six emotions (i.e., happiness, sadness, anger, disgust, fear, and surprise) as the basic discrete emotions. Thirty eight college students participated in the present study. Twelve slides (2 for each emotion category) were presented to the subjects in random order. During resting period of 30 s prior to the presentation of each slide, four presentation of each slide, four physiological measures (EEG, ECG, EDA, and respiration) were recorded to establish a baseline. The same physiological measures were recorded while each slide was being presented for 60 s (producing an emotional sate). Then, the subjects were asked to rate the degree of emotion induced by the slide on semantic differential scales. This procedure was repeated for every slide. Based upon the results, a model of emotion-specific physiological response patterns was developed: four emotion (fear, disgust, sadness, and anger) were classified according to the characteristics of EEG and autonomic responses. However, emotions of happiness and surprise were not distinguished by any combination of the physiological measures employed in this study, suggesting another appropriate measure should be adopted for differentiation.

• Asian Journal for Public Opinion Research
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• v.2 no.4
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• pp.248-278
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• 2015

Despite the proliferation of studies on emotion, little attention has been paid to the effects of discrete emotion on political participation. Using a representative survey conducted on a sample of South Korean citizens in the aftermath of the Sewol ferry accident, the current survey explored how anger and sadness, as well as the ways people express those emotions, influence the orientation of their response in social environments and, ultimately, their voting intention. The results partially supported the discrete effects of sadness and anger in eliciting reactions of approach or avoidance. Anger was found to provoke an approach action tendency in independent voters and supporters of the opposition, while also eliciting an avoidance action tendency with a varying effect size across all three groups of respondents. Sadness also prompted an approach action tendency in independents and supporters of the incumbent party, while it manifested a negative association with the avoidance action tendency in supporters of the opponent party. An interpretation of the findings and proposed directions for future research are presented.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.301-311
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• 2017

The current study investigated whether individual variation in motivational activation would predict the drug-use and interacts with discrete emotions to influence the responses to anti-drug advertisements. Motivational activation tendency indicates an individual's level to approach life-sustaining elements and defend life-threatening stimuli. Discrete emotion represents joy, sadness, and fear elicited by the advertisements. The experiment proceeded using both self-reports and physiological responses with 80 subjects. Results showed that approach motivation activation can be a target for anti-drug advertisements and in order to target individuals higher in approach activation, it is necessary to use the appeal type to elicit positive emotions such as joy.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.224-227
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• 1997

The International Affective Picture System (IAPS) developed by Lang and colleagues[1] is a world-widely adopted tool in studices relating a variety of physiological indices to subjective emotions induced by the presentation of standardized pictures of which subjective ratings are well established in the three dimensions of pleasure, arousal and dominance. In the present stuey we investigated whether distinctive EEG characteristics for six discrete emotions can be discernible using 12 IAPS pictures that scored highest subjective ratings for one of the 6 categorical emotions, i. e., happiness, sadness, fear, anger, disgust, and surprise (Two slides for each emotion). These pictures as visual stimuli were randomly given to 38 right-handed college students (20-26 years old) with 30 sec of exposure time and 30sec of inter-stimulus interval for each picture while EEG signals were recorded from F3, F4, O1, and O2 referenced to linked ears. The FFT technoque were used to analyze the acquired EEG data. There were significant differences in RP value changes of EEG bands, most prominent in theta, between positive positive and negative emotions, and partial also among negative emotions. This result is in agreement with previous studies[2, 3]. However, it requires further studied to decided whether IAPS could be a useful tool for catigorical approaches to emotion in addition to its traditional uwe, namely dimensional to emotion.

• Asian Journal for Public Opinion Research
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• v.10 no.2
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• pp.76-101
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• 2022

Despite the increasing use of digital media and their powerful impact on risk management during recent outbreaks of emerging infectious diseases, the question of how digital media exposure influences preventive behaviors has not been fully explained. Using the appraisal tendency framework and protection motivation theory as theoretical frameworks, we theorized the affective and cognitive mechanisms under which the differential roles of three negative emotions (fear, anger, worry) on two cognitive appraisals (perceived threat and perceived efficacy) were examined. Based on data collected from a survey of 1,500 South Koreans during the COVID-19 pandemic, we found that while worry and anger increased perceived efficacy, fear reduced perceived efficacy. The results also showed that although exposure to COVID-19 information via digital formats increased preventive behavioral intention in general, digital media use for COVID-19 information had a negative influence on preventive behavioral intention through the sequential mediation of fear and perceived efficacy.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2E
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• pp.74-78
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• 2006

This paper proposes an effective method for classifying emotions of the music from its acoustical signals. Two feature sets, timbre and tempo, are directly extracted from the modified discrete cosine transform coefficients (MDCT), which are the output of partial MP3 (MPEG 1 Layer 3) decoder. Our tempo feature extraction method is based on the long-term modulation spectrum analysis. In order to effectively combine these two feature sets with different time resolution in an integrated system, a classifier with two layers based on AdaBoost algorithm is used. In the first layer the MDCT-driven timbre features are employed. By adding the MDCT-driven tempo feature in the second layer, the classification precision is improved dramatically.

• Proceedings of the IEEK Conference
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• summer
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• pp.92-96
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• 2004

The researches of the emotions are currently great interest in speech processing as well as in human-machine interaction domain. In the recent years, more and more of researches relating to emotion synthesis or emotion recognition are developed for the different purposes. Each approach uses its methods and its various parameters measured on the speech signal. In this paper, we proposed using a short-time parameter: MFCC coefficients (Mel­Frequency Cepstrum Coefficients) and a simple but efficient classifying method: Vector Quantification (VQ) for speaker-dependent emotion recognition. Many other features: energy, pitch, zero crossing, phonetic rate, LPC... and their derivatives are also tested and combined with MFCC coefficients in order to find the best combination. The other models: GMM and HMM (Discrete and Continuous Hidden Markov Model) are studied as well in the hope that the usage of continuous distribution and the temporal behaviour of this set of features will improve the quality of emotion recognition. The maximum accuracy recognizing five different emotions exceeds $88\%$ by using only MFCC coefficients with VQ model. This is a simple but efficient approach, the result is even much better than those obtained with the same database in human evaluation by listening and judging without returning permission nor comparison between sentences [8]; And this result is positively comparable with the other approaches.

• Journal of Distribution Science
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• v.19 no.7
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• pp.51-59
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• 2021

Purpose: Anger has become one of the dominantly experienced emotions in recent years, particularly under the COVID-19 pandemic. Considering the critical role that anger plays in consumers' lives, the present research examines how feeling angry about money influences consumers' spending and money distribution decisions. Research design and methodology. Three experiments were conducted using different emotion induction methods (i.e., dictator game, autobiographical recall, and scenario). Results. Feeling angry about money decreased pro-social spending (i.e., less money distribution to the others), but it did not affect virtuous or utilitarian spending for the self-unlike past finding on negative feelings that increased utilitarian spending. Furthermore, whereas anger-tainted money decreased pro-social spending of that money, guilt-tainted money increased pro-social spending. However, the effects of guilt versus anger were not completely symmetrical. The antagonistic effect of anger was diffusive across spending on distant and close others, whereas the pro-social effect of guilt was limited to distant others. Conclusions: These findings help policy makers and financial institutions forecast how money will be distributed or circulated when it is likely to be dampened by anger under the pandemic. They also highlight the importance of examining the effects of discrete emotions (e.g., anger vs. guilt) beyond valence.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.197-203
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• 2005

In this paper, we propose an emotion recognition using facial Images to effectively design human interface. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition for the facial images is performed after applying the discrete wavelet. Here, the feature vectors are extracted from the PCA and LDA. Experimental results show that human emotions such as happiness, sadness, and anger has better performance than surprise, fear and dislike. Expecially, Japanese shows lower performance for the dislike emotion. Generally, the recognition rates for Korean have higher values than Japanese cases.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.105-120
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• 2012

This study aimed to develop a Korean emotion vocabulary list that functions as an important tool in understanding human feelings. In doing so, the focus was on the careful extraction of most widely used feeling words, as well as categorization into groups of emotion(s) in relation to its meaning when used in real life. A total of 12 professionals (including Korean major graduate students) partook in the study. Using the Korean 'word frequency list' developed by Yonsei University and through various sorting processes, the study condensed the original 64,666 emotion words into a finalized 504 words. In the next step, a total of 80 social work students evaluated and classified each word for its meaning and into any of the following categories that seem most appropriate for inclusion: 'happiness', 'sadness', 'fear', 'anger', 'disgust', 'surprise', 'interest', 'boredom', 'pain', 'neutral', and 'other'. Findings showed that, of the 504 feeling words, 426 words expressed a single emotion, whereas 72 words reflected two emotions (i.e., same word indicating two distinct emotions), and 6 words showing three emotions. Of the 426 words that represent a single emotion, 'sadness' was predominant, followed by 'anger' and 'happiness'. Amongst 72 words that showed two emotions were mostly a combination of 'anger' and 'disgust', followed by 'sadness' and 'fear', and 'happiness' and 'interest'. The significance of the study is on the development of a most adaptive list of Korean feeling words that can be meticulously combined with other emotion signals such as facial expression in optimizing emotion recognition research, particularly in the Human-Computer Interface (HCI) area. The identification of feeling words that connote more than one emotion is also noteworthy.