• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.61-72
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• 2018

Different types of traditional Korean clothes (Hanbok) are appearing in the market with the increasing interest of culture consumers. In order to turn traditional Korean clothes into everyday clothes that adequately reflect various demands of culture consumers, it is important to satisfy both functional and emotional aspects of clothing. However, there is lack of existing studies on emotions of culture consumers while wearing traditional Korean clothes. In this study, 28 emotional words regarding traditional Korean clothes were extracted by applying the Delphi method and conformity rating survey to 182 emotional words reported in existing studies and references from areas such as psychology, linguistics, and sensibility engineering. The 28 selected emotional words can be used to express emotions felt by culture consumers about traditional Korean clothes. Also, words were grouped based on the correlation according to factor analysis. Based on common characteristics, the emotional words were classified into 6 categories of 'pleasure,' 'aesthetic sense,' 'harmony,' 'novelty,' 'likability,' and 'stability.' These 6 emotional categories were concluded to represent emotions of consumers about traditional Korean clothes. The 28 emotional words and 6 representative emotions noted in this study can be used as basic data for measuring emotions of culture consumers of traditional Korean clothes. A future study task is to design a detailed assessment scale to measure emotions of culture consumers about traditional Korean clothes using representative emotions.

• 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 Korea Society of Design Studies Conference
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• 2005.10a
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• pp.52-53
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• 2005

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.2
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• pp.255-273
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• 2019

Perceptions of beauty change and are shared with others in the media of emotional words. In the modern age, a mix of traditional and modern make-up cultures has changed the standards of beauty. Therefore, an analysis using emotional words (an image that consumers have for certain subjects) and an image scale that intuitively shows them can be an important means for understanding changes in the "beauty of the time". This paper considered changes in typical aesthetic characteristics that women pursued through make-up by analyzing emotional words in white make-up powder advertisement texts from the 1920s through the 1930s. Imported modern technologies changed cosmetic manufacturing techniques and advertising methods to create a momentum that changed women's make-up culture from light to heavy make-up or from white to color make-up. Such changes have led to changes in the perception of beauty and were expressed through sensitive vocabularies such as pure, new, fresh, lofty, lively, healthy, and cheery. Such changes reflect social aspects such as women's aspirations for high status, pursuit of security, or women's roles under the wartime regime to show a change from beauty with an attribute of [+cool] to that of [+soft].

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.69-76
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• 2015

User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.43-48
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• 2008

And this study intends to discuss especially the one using emotional filter among various information processing methods. The existing music recommendation service on the web has a weak point that it makes the user feel bored by recommending songs only with similar feeling of the same genre, because music is classified by tune, melody, atmosphere and genre before recommendation. The service using emotion filter, suggested in this study, recommends the song and lyrics appropriate to the current emotional state of the user by abstracting emotional words that could reflect the sensitivity of human and then search the words within lyrics to match in order to overcome the weak point of the existing service. This study starts where the current emotional status for the user is being input. As for the range to choose, there are the seven representatives of emotion which are, love, separation, joy, sorrow-gloom, happiness-lonesome, and anger. As the service receives input of user's emotion, it matches the emotional words appropriate for the emotion input with the lyrics, and ranks the lyrics in the order of priority, so that it recommends the song and it lyrics to the user.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.46-49
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• 2008

This study aims to suggest basic materials to develop an emotional font for future Hangeul font development plan by investigating emotional reaction displayed through the subjects and by quantifying its contribution of the stimulation elements causing such reaction. For this, a survey of 150 university students who are currently enrolled in the College of Design was conducted in order to analyze correlation between 30 emotional words extracted from the Hangeul font and the selected 36 sample fonts. The combined data was described with the two dimensional dispersion using the quantification theory type III. The analysis found out that the Hangeul font forms the x-axis showing "soft(dynamic).hard(static)" and the y-axis showing "modern(light).classic(heavy)”. Specifically, there exist emotional groups such as "archaic","masculine","feminine","negative", and "modern static"on each axis. In addition, to extract the casual relationship between the value of emotional reaction and its stimulation elements quantitatively, the author indicated the emotional words of each axis and the total value of equivalent five emotional word groups as the standard variance and the constituent of Hangeul font as the independent variable, and then the quantification theory type I was used to analyze the physical elements of the Hangeul font. As a result, "the centerline of gravity(base line)" and "thickness variance of a stroke" on the two axes, and "the centerline of gravity(base line)" and "decoration" among the five groups were identified as the most influential elements that affect the emotional reaction of the subjects.

• Korean Institute of Interior Design Journal
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• v.19 no.6
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• pp.83-90
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• 2010

Emotional interest in the 1970s, Japan started from the technical and engineering beyond the scope, period late structuralist entering the world has been the subject of interest, as well as in academic research is becoming the main theory. In addition, communication between various disciplines such as humanities through the study of consilience and fusion, the human life to continue as a subject, its importance has risen. So this study are to design for the study of emotion through the human heart in space and how the expression of emotions and can be validated in a study. GSD to evaluate the action (verb) and emotional words (adjective) related to two variables to measure the degree of correlation coefficient was an experiment to find out. Picasso painting, it is 'difficult to understand', 'special', 'interesting', 'not interested', 'confused', 'fun', 'anxious', 'dark', 'cool', 'hard' to have relevance, such as the distribution of emotional words, and as a result of the move was a lot of work. This result can be obtained through the arcane resistance of the cubist paintings that make a lot of body movements. In Renoir painting 'stable', 'warm', 'soft', 'easy to understand', 'bright', 'boring', 'curious', such as emotional words ranged to have a relationship with this behavior is less motion in space. This result can be obtained through the understanding of the Impressionist paintings that are less body movements. As a result, space design, emotional design in the evaluation (GSD) for the empirical analysis that evaluated the feasibility and future of the emotional space of the design could be based in the area is considered.

• The Journal of Information Systems
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• v.29 no.3
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• pp.237-251
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• 2020

Purpose The research was studied the hierarchical Hangul emotion index by organizing all the emotions which SNS users are thinking. As a preliminary study by the researcher, the English-based Plutchick (1980)'s emotional standard was reinterpreted in Korean, and a hashtag with implicit meaning on SNS was studied. To build a multidimensional emotion dictionary and classify three-dimensional emotions, an emotion seed was selected for the composition of seven emotion sets, and an emotion word dictionary was constructed by collecting SNS hashtags derived from each emotion seed. We also want to explore the priority of each Hangul emotion index. Design/methodology/approach In the process of transforming the matrix through the vector process of words constituting the sentence, weights were extracted using TF-IDF (Term Frequency Inverse Document Frequency), and the dimension reduction technique of the matrix in the emotion set was NMF (Nonnegative Matrix Factorization) algorithm. The emotional dimension was solved by using the characteristic value of the emotional word. The cosine distance algorithm was used to measure the distance between vectors by measuring the similarity of emotion words in the emotion set. Findings Customer needs analysis is a force to read changes in emotions, and Korean emotion word research is the customer's needs. In addition, the ranking of the emotion words within the emotion set will be a special criterion for reading the depth of the emotion. The sentiment index study of this research believes that by providing companies with effective information for emotional marketing, new business opportunities will be expanded and valued. In addition, if the emotion dictionary is eventually connected to the emotional DNA of the product, it will be possible to define the "emotional DNA", which is a set of emotions that the product should have.

• Korean Journal of Cognitive Science
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• v.25 no.4
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• pp.385-416
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• 2014

In this study, memory for emotional words was compared between extraverts and introverts, employing signal detection analysis to distinguish differences in discriminative memory and response bias. Subjects were presented with a study list of emotional words in an encoding session, followed by a recognition session. Effects of task difficulty were examined by varying the nature of the encoding task and the intervals between study and test. For an easy task, with a retention interval of 5 minutes (Study I), introverts exhibited better memory (i.e., higher d') than extraverts, particularly for low-frequency words, and response biases did not differ between these two groups. For a difficult task, with a one-month retention period (Study II), performance was poor overall, and only high-frequency words were remembered; also extraverts adopted a more liberal criterion for 'old' responses (i.e., more hits and more false alarms) for positive emotional-valence words. These results suggest that as task difficulty drives down performance, effects of internal control processes become more apparent, revealing differences in response biases for positive words between extraverts and introverts. These results show that extraversion can distort memory performance for words, depending on their emotional valence.