• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.506-509
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• 2017

Opinion mining is a way to analyze the emotions in the text and is used to identify the emotional state of the author and to find out the opinions of the public. As you can analyze individual emotions through opinion mining, if you analyze the text by region, you can find out the emotional state you have in each region. The regional sentiment analysis can obtain information that could not be obtained from personal sentiment analysis, and if a certain area has emotions, it can understand the cause. For regional sentiment analysis, we need text data created by region, so we need to collect data through Twitter crawling. Therefore, this paper designs a Twitter data collection system for regional sentiment analysis. The client requests the tweet data of the specific region and time, and the server collects and transmits the requested tweet data from the client. Through the latitude and longitude values of the region, it collects the tweet data of the area, and it can manage the text by region and time through collected data. We expect efficient data collection and management for emotional analysis through the design of this system.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.720-729
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• 2021

The purpose of this study was to measure repeated the process of non-suicidal self-injury individuals change in everyday life through the Ecological Momentary Assessment(EMA) daily diary. The study subjects of were 17 adults aged 19 to 29, accessed a link sent by text message on a cell phone and recorded a diary of the day's affects, interpersonal conflicts, self-injury thoughts, and behaviors once a day for two weeks. Using a total of 238 reported entries, the contextual factors of NSSI were examined, and the effects of affects and interpersonal conflicts on NSSI analyzed through a multi-level model. As a result, the negative affects of that day have a significant relation with within subject NSSI behavior and positive affects have a significant relation between subject NSSI behavior. These findings means that overall individuals with low positive affects have a higher risk of self-injury behavior compared to those with higher levles of positive emotions, and an increase in negative emotions on that day within an individual increases the risk of self-injury behavior on that day. In other words, it implies that it is important to manage negative emotions and strengthen overall positive affects for that day in the intervention of emotion-regulation of experienced self-injury individuals. It is meaningful that this study explored NSSI risk factors experienced in daily life through the short-term longitudinal study.

• Journal of Ethics
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• no.84
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• pp.217-242
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• 2012

This essay aims to explore the importance of ethics education in Korean multicultural society. In 2011, it is reported by the Ministry of Education, Science and Technology that the final goal of Korean multicultural ethics education is to establish the foundations of National identity and of moral values in general. It might be a ideological tool, however, that can suppress the minority in Korea. In that sense, an orientation of ethics education in Korean multicultural society is basically to consider all moral agents in ethics. To give any solution, therefore, an attention will be paid to the notions of emotion and the likeness of moral fibre. Most important is that we have certain emotions which are in society beyond individual feelings. It is the only ethical subject and existence who we can have them. In that point, having them enables us to make any decision on the ground of moral values. By the quality of the likeness of moral fibre, furthermore, we can recognize and exercise moral values together without any difference in multicultural society. This makes sense of an identity as a Korean. Therefore, having emotions is helpful in taking the moral foundations of Korean multicultural society and the self-recognition of a Korean in the sense of the likeness of moral fibre give an ethical direction to us, the Korean multicultural society of ethical culture in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• Korean Journal of Adult Nursing
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• v.22 no.1
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• pp.19-30
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• 2010

Purpose: The purpose of the study was to describe psychosocial difficulties experienced by cancer patients. Methods: Three focus group interviews were conducted to collect the data from 19 outpatients with cancer undergoing treatments during 2009. All interviews were audio-recorded and transcribed verbatim. The data were analyzed using constant comparative analysis of grounded theory. Results: As a result of constant comparative analysis, 'psychosocial distress' was identified as a core category, and seven subcategories were identified. 'Plunged into negative emotions' and 'damaged self-identity' were identified as major categories in the individual dimension. 'Difficulty in dealing with diagnosis' and 'hasty expectations and concerns' were identified in the dimension of family. 'Inefficient communication' and 'lack of necessary information' were identified in the dimension of health care setting. 'Lonely journey into a strange territory' was identified in the dimension of society. Conclusion: The results of the study indicate that cancer patients experience a wide range of psychosocial problems. Thus, in assessing and relieving psychosocial distress of cancer patients, it is necessary to focus not only on the level of the individual but also on the levels of family, health care setting, and society in general is necessary.

• The Research Journal of the Costume Culture
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• v.8 no.5
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• pp.629-637
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• 2000

This paper focuses on the development of a fashion design educational program that will foster the talent and aesthetic consciousness of fashion design students. The goal of progressive educational methods with cutting edge technology is to elevate educational efficiency, and ultimately rear creative designers. To fulfill its objective, this paper presents a courseware program on fashion design education utilizing hyper media that include animation, photographs, pictures, sounds and characters. By the utilization of such comprehensive source of information media, a hypermedia courseware was developed for elementary education in fashion design with the following conclusions : 1. The program enables the students to customize their fashion design education. The students of fashion design education programs are able to choose and adjust their own programs to suit their requirements and intellectual level. 2. The program effectively motivates. Much like a constant sequence of various images on a screen that can provoke profound heart-felt emotions and inspire creativity, the program can stimulate and motivate the students. 3. The program provides a consistent education. To advance the overall quality of fashion design education, the problem of dissonance in educational content should be resolved and possible individual errors in delivery rectified. The present program will solve such problems, and establish coherent standards that will withstand the test of time regardless of time or place. 4. The program is cost effective. Since the present program frees the teacher from the time consuming drudgery of preparing various texts and lesson plans, have the materials delivered and handled, it reduces the time and cost previously required. 5. The program has the capability to be upgraded. The accumulated know-how of teachers and the total experience of the program can be linked with other programs for limitless expansion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.357-369
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• 2018

This paper aims at understanding the conceptual definition and the characteristics of happiness of korean university students. We analyzed the data using Hybrid model introduced by Schwartz-Barcott and Kim. The data was conducted from June, 2018 to July 2018. The participants in this study were 13 and an another part of the data was obtained from literatures regarding happiness of university students. We categorized Happiness of korean university students into eight attributes in four dimensions. In other words, The concept of happiness on korean university students is as follows: (i) Satisfaction of Individual's subjective, (ii) Satisfaction of Individual's objective, (iii) Achievement of goal, (iv) A positive cognition for the future, and (v) Relationship satisfaction from meaningful person, (vi) Physical and mental well-being of oneself and meaningful person, (vii) Satisfaction of everyday life, (viii) Satisfaction of college life. The major contribution from this paper is that we provide a guideline for establishing a strategy to reduce negative emotions and increase happiness of university students in korea by identifying the concept of Happiness on Korean university students. Based on this study, we recommend to develop an educational program to increase happiness of university students in korea.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.26 no.2
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• pp.199-209
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• 2019

Purpose: This study was conducted to determine factors affecting the positive feelings and care burden of elderly residents' primary caregivers in long-term care facilities. Methods: The survey was conducted between November and December 2018. A structured questionnaire was used to collect data, and 148 individuals voluntarily participated. The collected data were examined through descriptive statistical analysis using SPSS WIN ver.24.0, t-test, one-way Anova $Scheff{\acute{e}}$ test, Pearson's correlation coefficient, and multiple regression. Results: Factors that significantly affected caregivers' positive feelings included caregivers' education level(${\beta}=-.32$, p<.001), social support(${\beta}=.31$, p<.001), care burden(${\beta}=-.29$, p=.001), and total support fee(not more than 1.5million won)(${\beta}=-.18$, p=.012). The explanation power was as high as 40.0%(Adj $R^2=.40$). Factors that significantly affected caregivers' burden included social support(${\beta}=-.25$, p=.002), positive feelings(${\beta}=-.25$, p=.002), elderly individual's religion(${\beta}=-.17$, p=.007), and elderly individual's marriage status(${\beta}=.17$, p=.021). The explanation power was as high as 45.0%(Adj $R^2=.45$). Conclusion: Our results suggest that it is necessary to increase social support for elderly residents' primary caregivers in long-term care facilities. This can be helpful to decrease burden and enhance positive feelings in caregivers. We should also collect caregivers' information as well to provide appropriate assistance.