• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.113-120
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• 2016

People use social media platforms such as Twitter to leave traces of their personal thoughts and opinions. In other words, social media platforms retain the emotions of the people as it is, and accurately understanding the emotions of the people through social media will be used as a significant index for disaster management. In this research, emotion type modeling method and emotional quotient quantification method will be proposed to understand the emotions present in social media platforms. Emotion types are primarily analyzed based on 3 major emotions of affirmation, caution, and observation. Then, in order to understand the public's emotional progress according to the progress of disaster or accident and government response in detail, negative emotions are broken down into anxiety, seriousness, sadness, and complaint to enhance the analysis. Ultimately, positive emotions are further broken down into 3 more emotions, and Russell emotion model was used as a reference to develop a model of 8 primary emotions in order to acquire an overall understanding of the public's emotions. Then, the emotional quotient of each emotion was quantified. Based on the results, overall emotional status of the public is monitored, and in the event of a disaster, the public's emotional fluctuation rate could be quantitatively observed.

• The Korean Journal of Community Living Science
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• v.20 no.2
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• pp.169-180
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• 2009

This study was performed to examine the emotion expectations and explanations of four participants(an actor, a recipient, a child observer, and an adult observer) in moral, social-conventional, and personal rule transgression situations. Six vignettes describing the rule transgressions were presented to 200 children who were either five or seven years old. The children were asked to predict and explain each participant's emotions. The children's emotion expectations were different depending on the domain of the rule transgressions and on the type of the participant. The actors were predicted to feel happy during all transgressions, while the recipients and two observers(a child and an adult) were predicted to feel unhappy. The seven-year-old children attributed more happiness to the actors, and more negative affect to the recipients compared to the five-year-olds. This result was inconsistent with the previous findings that older children attributed more happiness to actors. This finding was discussed in relation to the 'happy victimizer'. Some categories of emotion explanations were differentiated according to the domain of rule transgressions. The personal rule transgressions, newly defined and examined in this study, were judged to be less serious than the moral rule transgressions in terms of the intensity of the negative affect.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.14 no.2
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• pp.13-24
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• 2010

Background and purpose: Seven Emotions consist of Joy(喜), Anger(怒), Anxiety(憂), Thought(思), Sorrow(悲), Fear(恐), Fright(驚). If Seven Emotion is excessive, its extreme mental stimulation causes physical illness. There was no study of the Seven Emotion Disease in detail for now. Therefore the purpose of this study is to pigeonhole the Seven Emotion Disease. Methods: We extract the sentences about the Seven Emotion and related words in Donguibogam. We classify the sententences into Joy(喜), Anger(怒), Anxiety(憂), Thought(思), Sorrow(悲), Fear(恐), Fright(驚), Frustration, Mental Exhaustion, Character. We analysis pattern of Symptoms Derived from Seven Emotions. Results and Conclusions Seven Emotion give rise to various type of symptom. In special Anger cause more illness than other Seven Emotion.

• Science of Emotion and Sensibility
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• v.24 no.3
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• pp.115-124
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• 2021

Non-verbal communication is important in human interaction. It provides a layer of information that complements the message being transmitted. This type of information is not limited to human speakers. In human-robot communication, increasing the animacy of the robotic agent-by using non-verbal cues-can aid the expression of abstract concepts such as emotions. Considering the physical limitations of artificial agents, robots can use light and movement to express equivalent emotional feedback. This study analyzes the effects of LED and motion animation of a spherical robot on the emotion being expressed by the robot. A within-subjects experiment was conducted at the University of Tsukuba where participants were asked to rate 28 video samples of a robot interacting with a person. The robot displayed different motions with and without light animations. The results indicated that adding LED animations changes the emotional impression of the robot for valence, arousal, and dominance dimensions. Furthermore, people associated various situations according to the robot's behavior. These stimuli can be used to modulate the intensity of the emotion being expressed and enhance the interaction experience. This paper facilitates the possibility of designing more affective robots in the future, using simple feedback.

• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.403-410
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• 2007

The most common method in the psychological measuring method for measuring user's emotions is to indirectly measure the user's emotion by using adjectives, called emotional words. The previous research, in order to observe user's emotional changes while they interact with a product, has extracted some emotional words and representative emotions, and made a set of subjective evaluation scale. In addition to adjective checklists, self-report questionnaire-type scales have been extensively used to assess user's emotions. This research suggested a self-report questionnaire-type scale using the representative emotions and a set of subjective evaluation scale made in the previous research. Also the reliability of the suggested self-report questionnaire-type scale was confirmed through the analysis of Cronbach's coefficient alpha. Therefore, the self-report questionnaire-type scale extracted through this research can be used in various ways to measure a user's user's emotions naturally expressed while using a product.

• MALSORI
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• no.62
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• pp.19-32
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• 2007

This study investigated the perception of emotional voices by transplanting some or all of the prosodic aspects, i.e. pitch, duration, and intensity, of the utterances produced with emotional voices onto those with normal voices and vice versa. Listening evaluation by 24 raters revealed that prosodic effect was greater than segmental & vocal quality effect on the preception of the emotion. The degree of influence of prosody and that of segments & vocal quality varied according to the type of emotion. As for fear, prosodic elements had far greater influence than segmental & vocal quality elements whereas segmental and vocal elements had as much effect as prosody on the perception of happy voices. Different amount of contribution to the perception of emotion was found among prosodic features with the descending order of pitch, duration and intensity. As for the length of the utterances, the perception of emotion was more effective with long utterances than with short utterances.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.6
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• pp.940-949
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• 2000

The purposes of this study were to examine the differences in consumers’perceived shopping situations by store format and to examine the effects of shopping situations on the within-store emotion and in turn on purchase behaviors of fashion products. Shopping situations included 16 general situations and 15 within-store situations, and four different store formats were selected for the study. Data were obtained from an on-site questionnaire survey to a convenience sample of young consumers. Four hundred fifty six responses were analysed. There were significant differences in shopping situations(3 general and 6 within-store) by store type. Eight shopping situations affected the within-store emotion, which, in turn, affected the purchase of fashion products.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.131-138
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• 2013

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym, and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1064-1070
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• 2020

In Korea, video-based news broadcasters are primarily classified into terrestrial broadcasters, general programming cable broadcasters and YouTube broadcasters. Recently, news broadcasters get subjective while targeting the desired specific audience. This violates normative expectations of impartiality and neutrality on journalism from its audience. This phenomenon may have a negative impact on audience perceptions of issues. This study examined whether broadcast news reporting conveys emotions and if so, how news broadcasters differ according to emotion type. Emotion types were classified into neutrality, happiness, sadness and anger using a convolutional neural network which is a class of deep neural networks. Results showed that news anchors or reporters tend to express their emotions during TV broadcasts regardless of broadcast systems. This study provides the first quantative investigation of emotions in broadcasting news. In addition, this study is the first deep learning-based approach to emotion analysis of broadcasting news.

• Anxiety and mood
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• v.18 no.2
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• pp.109-115
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• 2022

Objective : The purpose of this study was to examine the influence of subscales of emotional intelligence on empathy in first-year medical students. Methods : A total of 215 first-year medical students were eligible for this study. Demographic factors (age, sex, and medical school entrance type) and measures for emotional intelligence and empathy, such as the Wong and Law Emotional Intelligence Scale and the Interpersonal Reactivity Index, were included in the survey. The relationship between emotional intelligence and empathy was analyzed by multiple linear regression, adjusting for age, sex, and entrance type. Results : The female students' level of emotional intelligence was higher than the male students for the self-emotional appraisal (p=0.029) and others' emotional appraisal (p=0.006) subscales. Meanwhile, the graduate-entry students scored higher for the use of emotion (p<0.001) and regulation of emotion (p=0.010) subscales than the direct-entry students. For empathy, the female students revealed a higher score in empathic concern (p=0.009) than the male students, and graduate-entry students scored higher than the direct-entry students in perspective taking (p=0.004) and empathic concern (p<0.001). The multiple linear regression analysis has identified significant influences of subscales of emotional intelligence on empathy: others' emotional appraisal on perspective taking (p<0.001), self-emotional appraisal (p=0.035) and regulation of emotion (p=0.023) on fantasy, others' emotional appraisal (p<0.001) and use of emotion (p=0.020) on empathic concern, and self-emotional appraisal (p=0.033) and regulation of emotion (p<0.001) on personal distress. Conclusion : This study's findings suggest that emotional intelligence may affect empathy in medical students, which can have implications for developing educational strategies to enhance empathetic attitudes in medical students.