• Korean Journal of Food Science and Technology
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• v.52 no.2
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• pp.172-176
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• 2020

Recently, it has been reported that the positive emotional responses from previously consumed food could be transferred to the new food, affecting the acceptance of the food. This study was conducted to develop emotional lexicons for evaluating consumers' emotional responses to the food. Focus group interviews were conducted using 15 Koreans and 23 Chinese consumers to elicit emotional terms for Korean food HMR products. Using 23 Chinese participants who did not participate in the previous interview, emotional terms were screened through discussions in an interview setting. An online survey among 50 Koreans and 50 Chinese was carried out to evaluate and verify the valence and arousal potential of the selected terms. Elicited emotional terms in these two countries had similar valence and arousal potentials. However, cross-cultural differences were also found, mostly in arousal potential. Therefore, interpretation should be done carefully when comparing emotional responses between Korean and Chinese subjects.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.137-142
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• 2024

User interface (UI) functions are distorted and appear as a dark pattern that intentionally deceives or entices users. Consumers who are unaware of dark patterns are constrained in their choices, resulting in unnecessary economic damage. In this study, we aimed to investigate consumers' various shopping emotions and behavioral intentions after recognizing dark patterns in online shopping malls through qualitative research methods. As a result of the study, the rate of perception differed slightly depending on the type of dark pattern, and it was found that it induced consumer emotions such as distrust of the company, user deception, and displeasure. It has been found that the behavior after recognizing the dark pattern shows passive behaviors such as vowing to prevent recurrence and warning acquaintances rather than actively protesting to the company and demanding compensation for damages.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.11a
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• pp.396-400
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• 1999

인간의 감성은 다차원적 감정으로 이루어져 있다. 본 연구는 감성의 2차원 구조를 근거로 쾌-불쾌, 각성-이완 2차원적 감성을 생리신호로 분류하고자 하였다. 20명 남녀 대학생을 참가시켜 자극을 2차원 감성자극(쾌(펜디향수), 불쾌(에탄올), 각성(싸이렌), 이완(가요))으로 정의하고, 2*2 자극제시로 감성을 유발하였다. 26명의 남녀대학생을 실험에 참가시켜 4가지 감성을 유발하여, 측정한 생리신호로는 중추신경계의 활동을 나타내는 EEG(f3, p3, f4, p4)를 측정하였으며, 자율신경계의 활동을 나타내는 ECG(lead II), GSR, SKT를 측정하였다. 각각의 측정한 신호들에 대한 t-test를 실시하여 유의성 있는 변수를 추출하였으며 추출된 변수는 EEG의 f3(beta), p3(delta, beta), f4(delta), p4(alpha), HRV의 HF, HF/LF, GSR의 rising time이었으며 2차원 감성을 분류하였다.

• Journal of IKEEE
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• v.21 no.4
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• pp.397-403
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• 2017

In the modern society, psychological diseases and impulsive crimes due to stress are occurring. In order to reduce the stress, the existing treatment methods consisted of continuous visit counseling to determine the psychological state and prescribe medication or psychotherapy. Although this face-to-face counseling method is effective, it takes much time to determine the state of the patient, and there is a problem of treatment efficiency that is difficult to be continuously managed depending on the individual situation. In this paper, we propose an artificial intelligence emotion management system that emotions of user monitor in real time and induced to a table state. The system measures multiple bio-signals based on the PPG and the GSR sensors, preprocesses the data into appropriate data types, and classifies four typical emotional states such as pleasure, relax, sadness, and horror through the SVM algorithm. We verify that the emotion of the user is guided to a stable state by providing a real-time emotion management service when the classification result is judged to be a negative state such as sadness or fear through experiments.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.980-990
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• 2008

This study tested how impulse buying behavior for apparel was related to hedonic consumption and impulse buying tendencies and emotion in the context of shopping. A total of 290 self-administered questionnaires were obtained from college students during scheduled classes. A structural equation model using a correlation matrix with maximum likelihood was estimated for examining the relationships among consumer tendencies of hedonic consumption and impulse buying, positive emotion, and impulse buying behaviors by LISREL 8.53. Findings showed that impulse buying behaviors for apparel could be classified into planned, reminded, and fashion-oriented impulse buying typologies. Hedonic consumption and impulse buying tendencies had significant effects on positive emotion. Positive emotion had a significant effect on planned, reminded, and fashion-oriented impulse buying for apparel. This study suggests that positive emotion plays an important role in determining impulse buying behaviors relevant to hedonic and impulse buying tendencies. Managerial implications for apparel retailers are discussed.

• The Journal of Bigdata
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• v.5 no.2
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• pp.201-213
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• 2020

Despite empirical research that the response to human risk is significantly influenced affective factors, the role of affective factors has been unexplored in information privacy research. This study aims to explore the privacy behaviors of location-based service (LBS) users from an affective point of view. Specifically, the study explored the relationship between three types of privacy threats (collection, hacking, secondary use), two affects (worry, anger), and a coping behavior (continuous use intentions). The structured survey was conducted with 552 users. In order to analyze the effect of the combination of perception of particular privacy threats and particular affects on the intention of continuous use, association rules, one of the data mining techniques, was employed. As a result, there was a difference in the intention to use according to the combination of the perception of risk and affect responses, and the most significant influence on the intention is when the second use of personal information was combined with anger. This study has significant theoretical contribution in that it includes affective factors in the research of information privacy users, complementing the biases of existing cognition-oriented approaches and providing a comprehensive understanding of privacy response behavior.

• 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.18 no.1
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• pp.53-58
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• 2020

Various imperative statements that can be represented in the way in which the product or service is used describe how or how to achieve the goals, or induce or prohibit a specific action. This study focuses on The Effects of age and type of imperative sentence (directive vs. declarative) on behavioral intention and recall. As a result of the experiment, older people who have shorter lives remaining access information in a more emotional way, so they have been rejected by directive (vs. declarative) statements that felt more negative feelings, resulting in lowered behavioral intention. Conversely, the negative feeling caused by directive statements increased salience of directive (vs. declarative) sentence for older people more, which in turn increased memory for older people. Process analysis showed that emotions when exposed to statements mediated these results. The results of this study show that in order to improve consumers' behavioral response and/or the performance of information processing, it is necessary to deeply consider their age and how to construct the statement.

• Korean Journal of Culture and Social Issue
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• v.25 no.2
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• pp.101-118
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• 2019

Alexithymia refers to a psychological deficit of identifying and describing one's feelings. It has benn reported that the level of alexithymia of East-Asians is generally higher than that of Western Europeans. Recently one research conducted in U.S. suggested that the interdependent self-construal from East-Asians' collectivism culture might be a cause of this cross-cultural difference. In the current study, we examined the relationship between the level of independent and interdependent self-construal of Korean college students and their level of alexithymia, as well as their ambivalence over emotional expressiveness and emotion suppression. The correlation analysis shows that the Korean students' alexithymia level does not correlate with their level of interdependent self-construal, but negatively correlates with their level of independent self-construal. Moreover, it is also correlated with the level of ambivalence over emotional expressiveness(AEE) and emotion suppression(ES). Thus, we setup a double-mediation model between the deficiency of independent self-construal and alexithymia via AEE and ES, and estimate mediation effects using Hayes and Preacher(2014)s' Process analysis. The results show that the deficiency of independent self-construal has a direct effect as well as indirect effects of AEE and ES on the alexithymia level. Further analysis on the indirect effects reveals that the mediation effect of AEE and the double mediation effect of ES via AEE are significant, but the mediation effect of ES is not significant. Current results imply that the interdependent self-construal from the traditional collectivistic culture may not cause Korean college students' problems on the emotional expression, but the relatively lower independent self-construal may cause them. The deficiency of independent self-constural may raise up the level of self-defensive ambivalence over emotional expressiveness and suppress emotional expression by themselves, which can result in alexithymia.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.129-146
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• 2010

System response times(SRTs) are getting important while increasing the function of system. In the past, most research studied SRTs on situation of computer usage. There are lacking the research on simple domain. This study focuses on behavioral and emotional effect on situation of cell phone usage(experience 1; independent variables: degree of SRTs, dependent variables: behavioral and emotional evaluation). And this study investigates the behavioral and emotional effect in same SRTs on different situation(experience 2; independent variables: degree of SRTs, usage mode, dependent variables: behavioral and emotional evaluation, stress, mental strain). The result indicated that long SRTs increased problem solving time and negative emotion. User evaluated the system differently according to usage mode after they performed the same task. In other word, if user had a strong goal, then they felt more negative emotion and mental effort than the user don't have a strong goal. In the goal mode group, it was important there are being of delay or not. This study demonstrated that SRTs and usage mode influence user's emotion and behavior performance in same task.