• Journal of the Korean Home Economics Association
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• v.40 no.10
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• pp.103-112
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• 2002

This study investigated the relation between preschoolers' emotion understanding and parents' emotion expressiveness and attitude toward children's emotion expressiveness. Subjects were ninety 3- to 5-year old children and their parents. Parents' emotion socialization was measured by PACES developed by Saami(1989) and FEQ developed by Harberstadt(1986). And preschoolers' identification of basic emotional expressions and expression of their own feelings and others' feelings in various situations were measured. Results revealed that 5-year-old children understood emotion better than 3-year-old children, and mother's positive emotion expression influenced children's emotion understanding. The results are consistent with recent research showing that parents emotion socialization may be important for preschoolers' emotion understanding.

• Korean Journal of Childcare and Education
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• v.13 no.3
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• pp.39-54
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• 2017

Objective: The purpose of this study was to examine natural groupings of the sub-factors of mother's reaction to children's negative emotions. The natural groupings were as follows; the emotion-coaching-reaction, the emotion-minimizing-reaction and oversensitive reaction. In addition, this paper also investigated individual differences in children's emotion regulation by clusters of sub-factors of mother's reaction to children's negative emotions. Methods: The subjects of this study consisted of 318 children. The data were analyzed using cluster analysis and one-way ANOVA. Results: The results suggested four proper clusters, according to the characteristics of mother's reaction to children's negative emotions. Cluster 1 was categorized as 'child centered-emotion coaching', cluster 2 was categorized as 'oversensitive-emotion coaching comorbid', cluster 3 was categorized as 'acception-emotion minimizing confused' and cluster 4 was categorized as 'emotion minimizing-unsupporting.' Additionally, the differences between Emotion regulations in each cluster showed distinct points of interest. In terms of the maladaptive emotion regulation, cluster 3 showed the highest level followed by cluster 4. And cluster 1 and 2 showed the lowest level. Conclusion/Implications: The results of this study helped to find a deeper understanding of the operation of specific clusters of mother's reaction to children's negative emotion and children's emotion regulation.

• Journal of Families and Better Life
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• v.32 no.3
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• pp.137-146
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• 2014

The aims of this study were to investigate the relationships among mothers' emotion expression, preschool children's temperament, and preschool children's emotion regulation. The participants in this study were 75 5-year-old children from five child-care centers located in Seoul. The collected data were analyzed using simple regression and hierarchical multiple regression. The major findings were as follows. First, mothers' positive emotion expression had a positive influence on children's effortful control, and mothers' negative emotion expression had a positive influence on children's negative affect. Second, mothers' positive emotion expression had a positive influence on children's emotion regulation, while mothers' negative emotion expression had a negative influence on children's emotion regulation. Last, the effect of mothers' positive emotion expression on children's emotion regulation was fully mediated by children's effortful control. Also, the effect of mothers' negative emotion expression on children's emotion regulation was partially mediated by children's negative affect. These results suggest that mothers' emotion expression and children's temperament may predict children's emotion regulation.

• Korean Journal of Child Studies
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• v.25 no.5
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• pp.179-191
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• 2004

An emotion inference task was used to investigate children's cognitive cuing by age, cue type, and situation-emotion fit. Subjects were 41 of 3-, and 5-year-old children from two different day-care centers in Seoul and Kyonggi province. Each child was individually interviewed with pictorial tasks. 5-year-old children demonstrated more cuing, thinking, and application responses than 3-year-old children. Particularly, they showed more situation and thinking responses in situation-emotion match than in situation-emotion mismatch. 3-year-old children showed more past-oriented responses than 5-year-old children. In the interpersonal cue story, there were more situation, past-oriented and thinking responses than in the interobjective ones. The interpersonal cue story produced more situation responses in situation-emotion match than in situation-emotion mismatch.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.3
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• pp.167-179
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• 2016

Online games, by a massive influx of many players, it has diverse situations in which emotion is generated. Emotion plays an important role that helps players to interact and immerse in game. In the previous games, simple structures are used to express emotion. By increasing the user's needs of emotion in the game, it is necessary to structure a various type of emotion. In this paper, the game components were classified as background, object, and character in order to analyze emotion structurally in game. We defined how to use the rule of emotion, and applied to League of legend, Cyphers and World of Warcraft which belong to the AOS genre. The AOS game is well-suited for analyzing emotion structure, because a various emotional changes and situations can arise in the game. Through this paper, it was discovered similarities emotion to be used in online games. It is expected to generalize the emotion in the game by analyzing the emotional structure of more games in future.

• Journal of Integrative Natural Science
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• v.13 no.3
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• pp.97-104
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• 2020

This study suggests the emotion space modeling and emotion inference methods suitable for personalized services based on psychological and emotional models. For personalized emotion space modeling taking into account the subjective disposition based on the empirical assessment of the personal emotions felt by the personalization process of emotion space was used as a decision support tool, the Analytic Hierarchy Process. This confirmed that the special learning to perform personalized emotion space modeling without considering the subjective tendencies. In particular to check the possible reasoning based on fuzzy emotion space modeling and sensitivity for the quantification and vague human emotion to it based on the inherent human sensitivity.

• Korean Journal of Child Studies
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• v.23 no.1
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• pp.37-54
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• 2002

The purpose of study was to examine child emotion regulation as a function of child's sex, temperament, mother's emotion regulation, and mother's parenting. The subjects were 386 mothers of fifth or sixth graders in Seoul and Kyonggi province. The data were gathered through questionnaires developed for the current study. The major findings were as follows: 1) There were significant sex differences in some categories of child's emotion regulation. 2) The more active the child's temperament, the child showed more negative emotion regulation(venting, aggressive expression, avoidance). 3) Mother's negative emotion regulation was significantly related to the child's negative emotion regulation. 4) There were significant correlations between mother's parenting and child's emotion regulation. That is, mother's positive parenting was related to child's positive emotion regulation. 5) The relationship between mother's emotion regulation and child's emotion regulation was mediated by mothers' parenting.

• 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.

• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.103-111
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• 2012

This paper is a basic study for making a system that can predict the success and failure of entertainment contents at the initial stage of production. It proposes the user's emotion modeling of dynamic narrative on entertainment contents. To make this possible, 1) dynamic narrative emotion model is proposed based on theoretical research of narrative structure and cognitive emotion model. 2) configuring the emotion types and emotion value, proposed model of three emotion parameter(desire, expectation, emotion type) are derived. 3)To measure user's emotion in each story event of dynamic narrative, cognitive behavior and description of user(film, game) is established. The earlier studies on the user research of conceptual, analytic approach is aimed of predicting on review of the media and user's attitude, and consequently these results is delineated purely descriptive. In contrast, this paper is proposed the method of user's emotion modeling on dynamic narrative. It would be able to contributed to the emotional evaluation of entertainment contents using specific information.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.174-180
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• 2022

Emotion recognition is an essential component of complete interaction between human and machine. The issues related to emotion recognition are a result of the different types of emotions expressed in several forms such as visual, sound, and physiological signal. Recent advancements in the field show that combined modalities, such as visual, voice and electroencephalography signals, lead to better result compared to the use of single modalities separately. Previous studies have explored the use of multiple modalities for accurate predictions of emotion; however the number of studies regarding real-time implementation is limited because of the difficulty in simultaneously implementing multiple modalities of emotion recognition. In this study, we proposed an emotion recognition system for real-time emotion recognition implementation. Our model was built with a multithreading block that enables the implementation of each modality using separate threads for continuous synchronization. First, we separately achieved emotion recognition for each modality before enabling the use of the multithreaded system. To verify the correctness of the results, we compared the performance accuracy of unimodal and multimodal emotion recognitions in real-time. The experimental results showed real-time user emotion recognition of the proposed model. In addition, the effectiveness of the multimodalities for emotion recognition was observed. Our multimodal model was able to obtain an accuracy of 80.1% as compared to the unimodality, which obtained accuracies of 70.9, 54.3, and 63.1%.