• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.148-153
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• 1998

향은 방향성 또는 휘발성 물질에 il해 코의 점막을 통해 흡입되어 여러 감성의 변화와 뇌파등 생체 신호의 변화를 초래하고 또한 풍부한 감성도 유발한다. 특히 기억력에 관련된 원시 감정을 유발하고 생체에서 나오는 phermone(페르몬)은 행동 양식까지 영향을 미친다. 또한 질환치료에도 적용되거나 증상의 경감, 예방효과 등을 보여주는 aromatherapy는 매우 유망한 분야이다. 본 연구에서는 이러한 페르몬 향과 aromatherapy에 사용되는 essential oil등을 이용하여 주관적 감성 평가를 실시하고 이를 통계분석하여 이들 여러 종류의 향들의 자극으로 유발되는 감성의 특징을 밝혀내고자 하였다. 둘째로 향의 선호도를 결정하는데 어떠한 감성요인이 작용하는지를 알고자 하였다. 실험에 사용된 향은 26종류이고 총 33명의 지원자가 참여하였다. 설문지는 18문항을 선별하여 4가지 유형으로 작성한 후 유형별로 데이타를 정리하여 베리막스의 요인분석, 회귀분석, 군집분석등을 이용하여 분석하였다. 베리 막스의 요인분석으로 감성 형용사를 비슷한 척도끼리 묶어 .괘한 감성을 결정하는 요인, 자극의 강도를 결정하는 요인, 이외의 다른 고풍스럽거나 현대적인 요인등 3개 요인으로 grouping하였다. 향의 선호도를 결정하는데 중요한 감성척도에서는 피검자 성별에 따라 차이가 있음을 보여주었다. 남성의 경우 황홀하다, 여성적이다인데 반해 여성인 경우 재적하다, 친숙하다라는 감성 척도가 중요하게 작용하였다. 또한 각 향별로 군집 분류하여 향의 종류를 구분할 수 있었으며 또한 각 향별 선호도를 결정하는 감성 척도도 구해 보았다. 또한 향의 분류에 따른 감성 척도의 특징을 성별로 관찰한 결과 페르몬 향인 경우 essential oil과 달리 성별의 차이가 나타났다. 결론적으로 후각을 자극하는 향물질로 유발된 감성 측정을 해 본 결과 성별에 따라 선호도를 결정하는 감성요인의 차이를 알 수 있었으며 또한 essential oil에서는 성별 차이가 없는데 반해 페르몬 향의 경우 성별의 차이를 나타내었다.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.53-58
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• 2013

온라인 소비자들은 amazon.com과 같은 온라인 상점 플랫폼에 상품 평가(리뷰: review) 글을 남김으로써 대상 상품에 대한 의견을 표현한다. 이러한 상품 리뷰는 다른 소비자들의 구매 결정에도 큰 영향을 끼친다는 관점에서 볼 때, 매우 중요한 정보원이라고 할 수 있다. 사람들이 남긴 의견 정보(opinion)를 자동으로 추출하거나 분석하고자 하는 연구인 감성 분석(sentiment analysis)분야에서 과거에 진행된 대다수의 연구들은 크게는 문서 단위에서 작게는 상품의 요소(aspect) 단위로 사용자들이 남긴 의견이 긍정적 혹은 부정적 감정을 포함하고 있는지 분석하고자 하였다. 이렇게 소비자들이 남긴 의견이 대상 상품 혹은 상품의 요소를 긍정적 혹은 부정적으로 판단했는지 여부를 판단하는 것이 유용한 경우도 있겠으나, 본 연구에서는 소비자들이 '어떤 관점'에서 대상 상품 혹은 상품의 요소를 평가했는지를 자동으로 추출하는 방법에 초점을 두었다. 본 연구에서는 형용사의 대표적인 성질 중 하나가 자신이 수식하는 명사의 속성에 값을 부여하는 것임에 주목하여, 수식된 명사의 속성을 추출하고자 하였고 이를 위해 WordNet을 사용하였다. 제안하는 방법의 효과를 검증하기 위해 3명의 평가자를 활용하여 실험을 하였으며 그 결과는 본 연구 방향이 감성분석에 있어 새로운 가능성을 열기에 충분하다는 것을 보여주었다.

• Cross-Cultural Studies
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• v.51
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• pp.329-356
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• 2018

Types of emotional expressions are comprised of vocabulary that describes emotion and composition of sentences to express emotion such as an exclamatory sentence and a rhetorical question, expressions of interjection, adverbs of attitude for an idea, and a style of writing. This study is focused on vocabulary that describes emotion and analyzes the aspect of translation when emotional expression of 'Kyo(驚)' is shown in "Kokoro". As a result, the aspect of translation for expression of 'Kyo(驚)' showed that it was translated to vocabulary as suggested in the dictionary in some cases. However, it was not always translated as suggested in the dictionary. Vocabulary that describes the emotion of 'Kyo(驚)' in Japanese sentences is mostly translated to corresponding parts of speech in Korean. Some adverbs needed to add 'verbs' when they were translated. Different vocabulary was added or used to maximize emotion. However, the corresponding part of speech in English was different from Korean. Examples of Japanese sentences expressing 'Kyo(驚)' by verbs were translated to expression of participles for passive verbs such as 'surprise' 'astonish' 'amaze' 'shock' 'frighten' 'stun' in many cases. Idioms were also translated with focus on the function of sentences rather than the form of sentences. Those expressed in adverbs did not accompany verbs of 'Kyo(驚)'. They were translated to expression of participles for passive verbs and adjectives such as 'surprise' 'astonish' 'amaze' 'shock' 'frighten' 'stun' in many cases. Main agents of emotion were showat the first person and the third person in simple sentences. Translation of emotional expressions when a main agent was the first person showed that the fundamental word order of Japanese was translated as in Korean. However, adverbs of time and adverbs of degree were ended to be added. The first person as the main agent of emotion was positioned at the place of subject when it was translated in English. However, things or causes of events were positioned at the place of subject in some cases to show the degree of 'Kyo(驚)' which the main agent experienced. The expression of conjecture and supposition or a certain visual and auditory basis was added to translate the expression of emotion when the main agent of emotion was the third person. Simple sentences without the main agent of emotion showed that their subjects could be omitted even if they were essential components because they could be known through context in Korean. These omitted subjects were found and translated in English. Those subjects were not necessarily human who was the main agent of emotion. They could be things or causes of events that specified the expression of emotion.

• Archives of design research
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• v.13 no.2
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• pp.95-102
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• 2000

The purpose of this study is to find out what is the preference of users according to the location of benches at urban community parks. This location of benches is seperated into 4 patterns according to arranging pattern of water space, a walk, pergola and shelter, greenspace. To investigate the visual preference is examined by analyzing visual volume of 4 patterns. Results are as follows; 1. Factor analysis by the total data showed that 5 factors explain 60.40 percent of total variance of the location of bench visual character. They were classified by the sensitive factor, visual factor, physical-individual factor, distinct factor, density factor. Among 5 factors, the sensitive factor which represented psychological reaction was appreciated to be highest. 2. Most of 20 items showed the following scores of mean values in sementic differential experiment : Spot 1->Spot 4-> 2-> 3. The mean values between arrangement place locational differences showed significantly, that could explain to be a violent contrast between the natural factors(weater space, green space, etc) and the artificial factors (around of pergola, shelter, etc)

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.55-64
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• 1997

In this paper, a fuzzy set based decision support system is designed for the color planning, that uses the linguistic image words of the space to be colored and progressively recommend the harmoneous colors for each objects in the space. The linguistic image words denotes various emotional effects of the colored space represented as the adjectives like 'romantic', 'beautiful', and so on. The search for object color should not destroy the overall image of the colored space and should be harmoneous with the previously determined object colors. The developed color planning system is composed of five subsystems; two dimentional graphic tools to draw the color space, the input system to receive the linguistic image words, the system to determine and recommend the main colcrs, the system to determine the harmonious colors and the system to adjust the determined wlor objects. We expect that the system can help designers and the persons who are not good at color design, and it can be applied to various color design such as interior, fashions, and product design.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.279-284
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• 2019

The purpose of this study is to investigate the direction of communication design through in-depth interviews on the topic of gender equality, which is an active theme of social issue happening worldwide, and to suggest a direction to provide better social issue communication direction. In order to do so, firstly, I researched case studies and investigated the characteristics of gender magazines such as If, Ferm and Womankind. Secondly, I conducted an empirical study of in-depth interviews to identify the emotional adjectives by women and men by different age groups from gender equality storytelling magazine experience. As a result, I was able to grasp two points necessary. First of all, for the gender equality content messages closely related to everyday stories level down the barrier and become easier to empathize with. Second of all, the more complex the social issues are, the more sustainable and credible if the content developed steadily and contingently. This study is meaningful in that it suggested a series of directions for communicating gender equality issues. Future research should complement the suggested directions for gender equality communication design and contribute to guiding further directions.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.197-217
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• 2018

Music is one of the most creative act that can express human sentiment with sound. Also, since music invoke people's sentiment to get empathized with it easily, it can either encourage or discourage people's sentiment with music what they are listening. Thus, sentiment is the primary factor when it comes to searching or recommending music to people. Regard to the music recommendation system, there are still lack of recommendation systems that are based on customer sentiment. An algorithm's that were used in previous music recommendation systems are mostly user based, for example, user's play history and playlists etc. Based on play history or playlists between multiple users, distance between music were calculated refer to basic information such as genre, singer, beat etc. It can filter out similar music to the users as a recommendation system. However those methodology have limitations like filter bubble. For example, if user listen to rock music only, it would be hard to get hip-hop or R&B music which have similar sentiment as a recommendation. In this study, we have focused on sentiment of music itself, and finally developed methodology of defining new index for music recommendation system. Concretely, we are proposing "SWEMS" index and using this index, we also extracted "Sentiment Pattern" for each music which was used for this research. Using this "SWEMS" index and "Sentiment Pattern", we expect that it can be used for a variety of purposes not only the music recommendation system but also as an algorithm which used for buildup predicting model etc. In this study, we had to develop the music recommendation system based on emotional adjectives which people generally feel when they listening to music. For that reason, it was necessary to collect a large amount of emotional adjectives as we can. Emotional adjectives were collected via previous study which is related to them. Also more emotional adjectives has collected via social metrics and qualitative interview. Finally, we could collect 134 individual adjectives. Through several steps, the collected adjectives were selected as the final 60 adjectives. Based on the final adjectives, music survey has taken as each item to evaluated the sentiment of a song. Surveys were taken by expert panels who like to listen to music. During the survey, all survey questions were based on emotional adjectives, no other information were collected. The music which evaluated from the previous step is divided into popular and unpopular songs, and the most relevant variables were derived from the popularity of music. The derived variables were reclassified through factor analysis and assigned a weight to the adjectives which belongs to the factor. We define the extracted factors as "SWEMS" index, which describes sentiment score of music in numeric value. In this study, we attempted to apply Case Based Reasoning method to implement an algorithm. Compare to other methodology, we used Case Based Reasoning because it shows similar problem solving method as what human do. Using "SWEMS" index of each music, an algorithm will be implemented based on the Euclidean distance to recommend a song similar to the emotion value which given by the factor for each music. Also, using "SWEMS" index, we can also draw "Sentiment Pattern" for each song. In this study, we found that the song which gives a similar emotion shows similar "Sentiment Pattern" each other. Through "Sentiment Pattern", we could also suggest a new group of music, which is different from the previous format of genre. This research would help people to quantify qualitative data. Also the algorithms can be used to quantify the content itself, which would help users to search the similar content more quickly.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.171-196
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• 2018

With the development of the web, two-way communication and evaluation became possible and marketing paradigms shifted. In order to meet the needs of consumers, web design trends are continuously responding to consumer feedback. As the web becomes more and more important, both academics and businesses are studying consumer emotions and satisfaction on the web. However, some consumer characteristics are not well considered. Demographic characteristics such as age and sex have been studied extensively, but few studies consider psychological characteristics such as regulatory focus (i.e., emotional regulation). In this study, we analyze the effect of web style on consumer emotion. Many studies analyze the relationship between the web and regulatory focus, but most concentrate on the purpose of web use, particularly motivation and information search, rather than on web style and design. The web communicates with users through visual elements. Because the human brain is influenced by all five senses, both design factors and emotional responses are important in the web environment. Therefore, in this study, we examine the relationship between consumer emotion and satisfaction and web style and design. Previous studies have considered the effects of web layout, structure, and color on emotions. In this study, however, we excluded these web components, in contrast to earlier studies, and analyzed the relationship between consumer satisfaction and emotional indexes of web-style only. To perform this analysis, we collected consumer surveys presenting 40 web style themes to 204 consumers. Each consumer evaluated four themes. The emotional adjectives evaluated by consumers were composed of 18 contrast pairs, and the upper emotional indexes were extracted through factor analysis. The emotional indexes were 'softness,' 'modernity,' 'clearness,' and 'jam.' Hypotheses were established based on the assumption that emotional indexes have different effects on consumer satisfaction. After the analysis, hypotheses 1, 2, and 3 were accepted and hypothesis 4 was rejected. While hypothesis 4 was rejected, its effect on consumer satisfaction was negative, not positive. This means that emotional indexes such as 'softness,' 'modernity,' and 'clearness' have a positive effect on consumer satisfaction. In other words, consumers prefer emotions that are soft, emotional, natural, rounded, dynamic, modern, elaborate, unique, bright, pure, and clear. 'Jam' has a negative effect on consumer satisfaction. It means, consumer prefer the emotion which is empty, plain, and simple. Regulatory focus shows differences in motivation and propensity in various domains. It is important to consider organizational behavior and decision making according to the regulatory focus tendency, and it affects not only political, cultural, ethical judgments and behavior but also broad psychological problems. Regulatory focus also differs from emotional response. Promotion focus responds more strongly to positive emotional responses. On the other hand, prevention focus has a strong response to negative emotions. Web style is a type of service, and consumer satisfaction is affected not only by cognitive evaluation but also by emotion. This emotional response depends on whether the consumer will benefit or harm himself. Therefore, it is necessary to confirm the difference of the consumer's emotional response according to the regulatory focus which is one of the characteristics and viewpoint of the consumers about the web style. After MMR analysis result, hypothesis 5.3 was accepted, and hypothesis 5.4 was rejected. But hypothesis 5.4 supported in the opposite direction to the hypothesis. After validation, we confirmed the mechanism of emotional response according to the tendency of regulatory focus. Using the results, we developed the structure of web-style recommendation system and recommend methods through regulatory focus. We classified the regulatory focus group in to three categories that promotion, grey, prevention. Then, we suggest web-style recommend method along the group. If we further develop this study, we expect that the existing regulatory focus theory can be extended not only to the motivational part but also to the emotional behavioral response according to the regulatory focus tendency. Moreover, we believe that it is possible to recommend web-style according to regulatory focus and emotional desire which consumers most prefer.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.2
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• pp.13-22
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• 2015

The study discovers mood state and enhancement effect of users by scenery of location targeting Seonyudo Park; where is widely recognized as the representative recycling environmental park as well as theme experience space and scenery admiration in Korea. Also, the influence level of park and thematic space upon wellness was researched for future park design and its base data. As a result of semantic differential(SD), the most items showed low point in positive way when people admiring the scenery in Seonyudo. Also, a subject experienced differently depending on each inside scenery element of the park. As a result of profile of mood states(POMS), a tension and anxiety points were shown in order of Urban (7.78) > Water Purification Basin(3.33) > Gardens of Water Plants(2.11) > Garden of Green Pillar(2.00) > Garden of Time (0.89). The depression points were shown in order of Urban(4.94) > Water Purification Basin(3.50) > Garden of Green Pillar(2.94) > Garden of Time(1.61) > Gardens of Water Plants(1.38). The anger and hostility points were shown in order of Urban(4.22) > Water Purification Basin(3.33) > Garden of Green Pillar(2.22) > Garden of Time(1.39) > Gardens of Water Plants(1.11). The fatigue points were shown in order of Urban(6.5) > Water Purification Basin(3.39) > Garden of Green Pillar(2.78) > Garden of Time(2.28) > Gardens of Water Plants (2.06). The vigor points were shown in order of Gardens of Water Plants(11.39) > Garden of Time(11.00) > Garden of Green Pillar(8.39) > Water Purification Basin(7.77) > Urban(5.28). Also, as a result of statistics analysis, difference value of scenery type is significant. The result of total emotional disturbance(TED) was analyzed in order of Urban(24.5) > Water Purification Basin(9.5) > Garden of Green Pillar(4.67) > Garden of Time(-1.39) > Gardens of Water Plants(-1.22).