• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.167-176
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• 2013

User-created text data are increasing rapidly caused by development of social media. In opinion mining, User's opinions are extracted by analyzing user's text. A primary goal of sentiment analysis as a branch of opinion mining is to extract user's opinions from a text that is required to build a list of emotion terms. In this paper, we built a list of emotion terms to analyse a sentiment of social media using Facebook as a representative social media. We collected data from Facebook and selected a emotion terms, and measured the dimensions of valence and activation through a survey. As a result, we built a list of 267 emotion terms including the dimension of valence and activation.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.1
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• pp.34-44
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• 2004

The purpose of this study was to provide effective design strategy and distinguish productions for the consumer's emotion satisfaction by analyzing formative properties of fashion sensibility and emotion. 54 photos of contemporary costume have been selected which represented the Izard' DES. The questionnaire consisted of bi-polar 25 pairs adjective scale of fashion sensibility and the 18 noun scale of emotion was distributed to 970 male and female living in Pusan area. The data were analyzed by GLM using the statistic SPSS package. The major findings of this research were as follows. 1. In the clothing formative properties following fashion sensibilities, aestheticism shows significant differences in the silhouette and texture, maturity in the silhouette and color, character in the texture and decoration and feminity in the pattern and color. 2. In the clothing formative properties following emotions, negative emotion shows significant differences in the pattern and silhouette, distressㆍfear in the silhouette and pattern, arousal in the texture and color, shame in the color and texture and enjoyment in the silhouette and pattern. 3. In the fashion sensibility and emotion following clothing formative properties, each formative property shows differences in fashion sensibility and emotion. This study result will be utilized in the clothing design development in special usage like theatrical costume, discriminated display and advertisement stratge.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.696-702
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• 2014

Recently, researches on analyzing relationship between the state of emotion and musical stimuli using EEG are increasing. A selection of feature vectors is very important for the performance of EEG pattern classifiers. This paper proposes a comparison of EEG feature vectors for emotion classification according to music listening. For this, we extract some feature vectors like DAMV, IAV, LPC, LPCC from EEG signals in each class related to music listening and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification according to music listening.

• Korean Journal of Cognitive Science
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• v.22 no.3
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• pp.299-326
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• 2011

The text such as stories, blogs, chat, message and reviews have the overall emotional flow. It can be classified to the text having similar emotional flow if we compare the similarity between texts, and it can be used such as recommendations and opinion collection. In this paper, we extract emotion terms from the text sequentially and analysis emotion terms in the pleasantness-unpleasantness and activation dimension in order to identify the emotional flow of the text. To analyze the 'dominant emotion' which is the overall emotional flow in the text, we add the time dimension as sequential flow of the text, and analyze the emotional flow in three dimensional space: pleasantness-unpleasantness, activation and time. Also, we suggested that a classification method to compute similarity of the emotional flow in the text using the Euclidean distance in three dimensional space. With the proposed method, we analyze the dominant emotion in korean modern short stories and classify them to similar dominant emotion.

• Korean Journal of Child Studies
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• v.20 no.1
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• pp.3-14
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• 1999

Seven textbooks for children used in homes and schools (sudangs) of the Chosun dynasty were examined to investigate how they taught emotional intelligence in traditional Korean society. The contents of the books were analyzed according to the 4 abilities of emotional intelligence described by Salovey and Mayer (1966): (1) perception, appraisal, and expression of emotion, (2) emotion's facilitation of thinking, (3) understanding and analyzing emotions, and (4) regulation of emotion to promote emotional and intellectual growth. The analysis showed that most of the books valued emotional intelligence and taught children how they perceive, appraise, and express emotions. The emotional ability to facilitate thinking was also emphasized, whereas the ability to understand and analyze emotions was seldom mentioned. It was also found that the regulation of emotion was emphasized; that is, children were educated to control and depress their emotions rather than to express them naturally.

• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.471-480
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• 2007

Negative emotions play an important function as to human's existence. In this research, we employed the audio-visual film clips to induce negative emotions and examined the classified responses in the autonomic nervous system(ANS) due to each negative emotion.30 adults(22.6 years $old{\pm}1.24$, 15 males and 15 females) took part in this experiment. Through the preliminary experiment, 2 minutes film's stimuli were selected as the emotion-induced stimuli. During the period when participants were viewing and listening to the selected movie, EDA and ECG were examined as soon as one stimulus was displayed, participants were tested by completing the psychological appraisals of their experienced emotion due to each emotional stimulus. With regard to the result of analyzing the psychological responses, each negative emotion appropriately and effectively induced its target emotion. While concerning the result of analyzing ANS responses, each negative emotion induced its respective activation in ANS. What is more, compared with other types of negative emotional stimuli, the scaring stimulus induced higher activation of the sympathetic nervour system(SNS) as to the indexes in EDh and ECG. This research made segmentation of ANS responses to each negative emotion, which has its significance.

• 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.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.151-154
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• 2008

The purpose of this research project is to provide information on emotional design and designs a kind of shoe storage for small space. Through researching the activities of target user and analyzing the present market, we get the clear understanding of direction for storage design, and create a new domain of for storages, with its added value and competition too. This will satisfy demand of consumers and benefit for enterprise.