• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.239-248
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• 2012

This paper looks to extract personality traits from the drama characters within a drama script, and to apply it them to a character that has an artificial emotion. The method of applying the personality of a character from a drama script is as follows. First, we separate a drama script into several pieces, by the characters therin. Next, we extract emotion-related terms by matching morphemes analysis and by using an emotion terms database. Next, we analyze a dominant emotion using extracted emotion terms. Finally last, we apply the analyzed dominant emotion to an equation pertaining to artificial emotion. We made progress in developing user evaluation that features blind testing, to verify that the artificial emotion character bears the personality of a drama character. We apply three drama character personalities to artificial emotion characters bearing the same appearance. The user had to match three artificial emotion characters and drama characters according to personality. The users had a high percentage of correct answers, thus confirming the efficacy of our method of applying a personality, using information from a drama script.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2004.11a
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• pp.22-22
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• 2004

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.444-465
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• 2013

The purpose of this study is to extract core situations that can arouse various academic emotions and to analyze the characteristics of intensity-frequency of these academic emotions from Korean elementary students in Science classes. To accomplish this study, authors conducted a survey of 642 sixth grade students. The result of the study are as follows: First, science academic emotions varied depending on each of the science learning situations. On the whole, positive-emotions were aroused in science experiment situations and negative-emotions were aroused in evaluation, personality of individuals and other people, teaching-learning method and science experiment situations. If teachers want to manage a specific emotion, they should control the core situations that can arouse that specific emotion. Second, positive-emotions appeared more than negative-emotions in intensity and frequency. But boredom, annoyance and stuffiness appeared the most among negative-emotions. Teachers have to reduce students' boredom, annoyance and stuffiness that are aroused in their science classes. Based on the results, authors become assured that introduction of the emotions was a very useful method in enhancing Korean elementary students' affective domain achievement in science classes.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2004.11a
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• pp.57-57
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• 2004

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2004.11a
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• pp.44-44
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• 2004

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.369-376
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• 2021

One of the most active areas of research in the field of affective computing and signal processing is emotion recognition. This paper proposes emotion recognition of low-resource (Sindhi) language. This work's uniqueness is that it examines the emotions of languages for which there is currently no publicly accessible dataset. The proposed effort has provided a dataset named MAVDESS (Mehran Audio-Visual Dataset Mehran Audio-Visual Database of Emotional Speech in Sindhi) for the academic community of a significant Sindhi language that is mainly spoken in Pakistan; however, no generic data for such languages is accessible in machine learning except few. Furthermore, the analysis of various emotions of Sindhi language in MAVDESS has been carried out to annotate the emotions using line features such as pitch, volume, and base, as well as toolkits such as OpenSmile, Scikit-Learn, and some important classification schemes such as LR, SVC, DT, and KNN, which will be further classified and computed to the machine via Python language for training a machine. Meanwhile, the dataset can be accessed in future via https://doi.org/10.5281/zenodo.5213073.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.97-104
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• 2012

Recently, a big text data has been produced by users, an opinion mining to analyze information and opinion about users is becoming a hot issue. Of the opinion mining, especially a sentiment analysis is a study for analysing emotions such as a positive, negative, happiness, sadness, and so on analysing personal opinions or emotions for commercial products, social issues and opinions of politician. To analyze the sentiment analysis, previous studies used a mapping method setting up a distribution of emotions using two dimensions composed of a valence and arousal. But previous studies set up a distribution of emotions arbitrarily. In order to solve the problem, we composed a distribution of 12 emotions through carrying out a survey using Korean emotion words list. Also, certain emotional states on two dimension overlapping multiple emotions, we proposed a selection method with Roulette wheel method using a selection probability. The proposed method shows to classify a text into emotion extracting emotion terms from a text.

• Mood & Emotion
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• v.10 no.1
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• pp.31-36
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• 2012

Objectives : The aim of this study was to investigate the relationship between depressive symptom, spiritual well-being and state hope in early adults and middle aged patients with depression. Methods : A total of 180 outpatient were surveyed with Beck Depression Inventory (BDI), Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale (FACIT-Sp) and The State Hope Scale (SHS). Mean scores of BDI, FACIT-Sp and SHS were compared between two groups of different age. Correlation analysis and multiple linear regression analyses were performed to identify the effect of BDI and FACIT on SHS according to age. Results : Mean scores of SHS and FACIT were higher significantly in middle aged group than early adults group, while BDI was not different between two groups. And early adults and middle aged patient's state hope showed a significantly negative correlation with spiritual well-being. In regression analysis, the effect of BDI, FACIT on SHS were significant in both groups and the regression model explained 42% of the variance of state hope in early adults group and 26% in middle aged group, respectively. Conclusion : These findings suggest that in depressive symptom and low state hope relationship, spirituality is important protective factor in both aged adult outpatients with depression.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.381-392
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• 2009

The aim of this study was to develop a research protocol that provides standardized conditioning stimuli in effectively evoking emotion-specific responses in children. The protocol targets five specific emotions(i.e., happiness, sadness, anger, distress, and boredom) by introducing study participants to a combination of music, color, stories, and dolls. This research protocol also includes a self-report emotion assessment scale specially developed for this study to verify the types of emotion induced. Evaluation of the method entailed triangulation of the results from the subjects' self-reported emotional state corresponding to each conditioned stimulus as well as behavioral observations conducted by researchers. Findings suggest that this new protocol effectively evokes five emotions in correspondence to the way it was intended for appropriate emotion induction. Additionally, results showed that female children than male children are more likely to feel boredom; and school-aged children were more likely to react to sadness than pre-school children.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.73-82
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• 2018

Attempts have been made to recognize social emotion, including competition-cooperation, while designing interaction in work places. This study aimed to determine the cardiac response associated with classifying competition-cooperation of social emotion. Sixty students from Sangmyung University participated in the study and were asked to play a pattern game to experience the social emotion associated with competition and cooperation. Electrocardiograms were measured during the task and were analyzed to obtain time domain indicators, such as RRI, SDNN, and pNN50, and frequency domain indicators, such as VLF, LF, HF, VLF/HF, LF/HF, lnVLF, lnLF, lnHF, and lnVLF/lnHF. The significance of classifying social emotions was assessed using an independent t-test. The rule-base for the classification was determined using significant parameters of 30 participants and verified from data obtained from another 30 participants. As a result, 91.67% participants were correctly classified. This study proposes a new method of classifying social emotions of competition and cooperation and provides objective data for designing social interaction.