• 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 Korean Classical Literature and Education
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• no.38
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• pp.139-173
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• 2018

In the study of Guunmong, which is one of the representative classical $17^{th}$ century novels of the Joseon Dynasty, interpretations through The Book of Change(Juyeok) have recently emerged. It is necessary to more concretely investigate the themes of the research. The writer Kim man-jung wrote the work in an exile situation. In that time he composed a poem using Chinese letters with meaning connected to The book of Change. In particular, the discourse of Bok-gwae(復卦, ䷗) concentrating on the meaning of recovery might be a basis to construct the inner world of the work. The sentence of 'Bok goes well' in The Book of Change suitably match up with the hero's life in Guunmong. In addition the sentences of 'There is no illness in going and coming. So it will be no faults if friends arriver' can be applied to the meeting between the hero and heroines of Guunmong. The general declarations of The Book of Change are appropriate for explaining the contents of Guunmong. There are six Hyos that make up Gwae. The Hyos, from the first one at the bottom to the fifth one up above, connect to the characters of Guunmong. The phrase of 'Not going far away' regarding to the first Yang Hyo can be connected to Yang So-yu, hero of Guunmong. The phrase of 'Recovering beautifully' with regard to the second Eum Hyo can also be realized in the life of Jeong Gyeong-pae and Ga Chunun, two heroines of the work. The phrase of 'Danger owing to frequently recovering' regarding the third Eum Hyo can be applied to the position of Gye Seom-weol and Jeok Gyeong-hong. The phrase of 'Going middle with recovering alone' regarding the forth Eum Hyo can be matched with Sim Yo-yeon and Baek Reung-pa. The phrase of 'No regrets during an intense recovery' with regard to the fifth Eum Hyo is applicable to Yi So-hwa and Jin Chae-bong. The phrase of 'Boding of a confused recovering' regarding the sixth Eum Hyo is related to the writer's situation. The boding of confused recovering is owing to anti-royal road. The contrast between the royal road and the anti-royal road reflects Confucianism and Buddhism, dream and reality, and Yang So-yu in a dream and Seong Jin, who is same hero, in reality. Moreover, the structure of Guunmong which is organized in the form of reality-dream-reality, has a basis in this contrast. Considering these relationships, we can say the classical novel Guunmong is a fable of Bok-gwae. The work is a hopeful narration of an effective recovery that the writer anticipated in exile.

• Korean Journal of Psychosomatic Medicine
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• v.14 no.1
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• pp.39-46
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• 2006

Objectives: The study was intended to explore the relationships between temperament and premenstrual dysphoric disorder, to understand symptomatology of premenstrual dysphoric disorder and associated personality trait and to suggest therapeutic availability. Method : Twenty eight women, diagnosed as premenstrual dysphoric disorder by DSM-IV, were asked to complete the Korean version of Tridimensional Personality Questionnaire, and Shortened Premenstrual Assessment Form. The correlations between the severity of premenstrual symptoms and the scores of Tridimensional Personality Questionnaire were calculated. Results : The severity of symptoms of premenstrual dysphoric disorder was best explained by the harm-avoidance factor of the four dimensions of temperament. Conclusion : The symptoms of premenstrual dysphoric disorder are well explained by the harmavoidance factor and the reward-dependence factor of four dimensions of the temperament.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.83-107
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• 2020

Selecting business charts based on the nature of the data and the purpose of the visualization is useful in business analysis. However, current visualization tools lack the ability to help choose the right business chart for the context. Also, soliciting expert help about visualization methods for every analysis is inefficient. Therefore, the purpose of this study is to propose an accessible method to improve business chart productivity by creating rules for selecting business charts from online published documents. To this end, Korean, English, and Chinese unstructured data describing business charts were collected from the Internet, and the relationships between the contexts and the business charts were calculated using TF-IDF. We also used a Galois lattice to create rules for business chart selection. In order to evaluate the adequacy of the rules generated by the proposed method, experiments were conducted on experimental and control groups. The results confirmed that meaningful rules were extracted by the proposed method. To the best of our knowledge, this is the first study to recommend customizing business charts through open unstructured data analysis and to propose a method that enables efficient selection of business charts for office workers without expert assistance. This method should be useful for staff training by recommending business charts based on the document that he/she is working on.

• Phonetics and Speech Sciences
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• v.11 no.2
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• pp.33-44
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• 2019

This paper dealt with how realization of pauses in utterance is affected by speech style, gender, and generation. For this purpose, we analyzed the frequency and duration of pauses. Pauses were categorized into four types: pause with breath, pause with no breath, utterance medial pause, and utterance final pause. Forty-eight subjects living in Seoul were chosen from the Korean Standard Speech Database. All subjects engaged in reading and spontaneous speech, through which we could also compare the realization between the two speech styles. The results showed that utterance final pauses had longer durations than utterance medial pauses. It means that utterance final pause has a function that signals the end of an utterance to the audience. For difference between tasks, spontaneous speech had longer and more frequent pauses because of cognitive reasons. With regard to gender variables, women produced shorter and less frequent pauses. For male speakers, the duration of pauses with breath was significantly longer. Finally, for generation variable, older speakers produced more frequent pauses. In addition, the results showed several interaction effects. Male speakers produced longer pauses, but this gender effect was more prominent at the utterance final position.

• Journal of Popular Narrative
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• v.26 no.1
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• pp.103-132
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• 2020

By analyzing the characteristics and meaning of dystopia in Korean juvenile science fiction, this study aims to search for the principles of juvenile literature responding to the contradictions of scientific technologism in collusion with state capitalism, and to consider its limitations and significance. This study focuses on the juvenile science fiction in which children or teenagers fight against system dystopia functioning as a setting of the story. System dystopia consists of 'fake utopia' and 'concentration camps' holding those excluded from this 'fake utopia'. Young people whose right to life are violated under the system dystopia escape from concentration camps and fight against political power. We don't have many novels that have focused on environmental dystopia, but a nomadic subject is found in works set on Earth after environmental pollution or nuclear explosion. In short, juvenile dystopia science fiction deepens the contradictions of the hierarchical society based on scientific technologism, criticizing the repressive, material-oriented and differential educational realities of our society. They hope that children or teenagers will act as a resistance that sees through the deception and hypocrisy of the social system. These works are significant in that they expose the biopolitics strategy of political power in collusion with industrial capitalism and induce us to reflect on it. However, it seems to be the limit of humanism to equate human life with nature and to warn of dangers of technology, machinery, and material civilization as the counterpart. This paper has the significance of taking a general survey of juvenile dystopia science fiction since the 2000s, and revealing the writers' perception of scientific technologism and its limitations.

• Journal of Popular Narrative
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• v.27 no.3
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• pp.127-150
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• 2021

This study focuses on analyzing the epic characteristics of a korean sports cartoon called "Burning Ground" in the 1970s. Through this, we would like to reveal that only "Burning Ground" has a unique narrative. We hope that such research will accumulate and serve as the basis for the study of Korean sports cartoon. In the 1970s and 1980s, Korean sports cartoons were narratives of the main characters. The story of the family is central to the narrative. Family revenge is mainly the central narrative. Plural narratives are serious, and sports act as auxiliary narratives. It uses 'Spocon', a characteristic of Japanese sports cartoons, to show its efforts to get revenge. Therefore, it is extremely rare to use professional knowledge in Korean sports cartoons in the 1970s. Burning Ground uses an escalating system to construct incremental narratives. The three-dimensional narrative is composed by utilizing various narratives of surrounding characters. The use of expertise in football is a feature of the 1990s, and showing this in the 1970s means that the work is ahead of its time. There are limitations of Japanese cartoon theft and plagiarism. However, through this, it provides evidence to examine the relationship between Korea and Japan. And timeless epic speciality must be recognized. The study is meaningful in that it can broaden the perspective of Korean cartoon research in the 1970s.

• Korean Journal of Culture and Social Issue
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• v.18 no.2
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• pp.235-260
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• 2012

This study was aimed at looking into and understanding child-rearing experience of mothers from multicultural families based on the grounded theory, one of the qualitative research methods. For this, twelve mothers from multicultural families were selected and data were collected through in-depth interviews with them and then analyzed through the open coding, axial coding and selective coding. The analysis suggested that main phenomena mothers from multicultural families experienced are the conflict of child-rearing and educational crisis, and the confused identity of parenting. These main phenomena had much to do with contextual factors such as economic hardship, lower level of the Korean language, cultural differences, prejudices and ignorance. The severeness of conflict and crisis of child-rearing and the intensity of identity confusion for parenting depended on arbitral conditions such as family bonds, positive expectation for the future of their children, and the help of supportive systems. Mothers were dealing with difficulties of child-rearing through action and interaction of resignation and denial, introspection and the intention to overcome difficulties, and the capacity building. As a result, mothers from multicultural families acknowledged that there is a limit to their position and roles they can play and tried to change in order to resolve problems related to their children, positioning themselves for more active lives in Korean society. Through discussion based on the findings of the study, this study can help better understand child-rearing experience of mothers from multicultural families and suggest several directions for future researches on multicultural families.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Sleep Medicine and Psychophysiology
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• v.9 no.2
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• pp.106-114
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• 2002

Objectives: Daytime sleepiness is a common symptom and is associated with sleep behavior, sleep deprivation, and night shift, etc. It is also one of the most important symptoms of sleep disorders like obstructive sleep apnea (OSA). According to our survey on Korean literature, a few studies have dealt with daytime sleepiness, and we have not been able to locate any study comparing normal subjects with polysomnography-proven sleep disorder patients regarding daytime sleepiness. We aimed at comparing daytime sleepiness among normal healthy daytime workers, medical students being expected to have daytime sleepiness due to chronic sleep deprivation, and patients having sleep disorders diagnosed with polysomnography. We also studied the association between subjective daytime sleepiness and objective polysomnographic findings in patients with sleep disorders. Methods: One hundred three hospital workers, 137 medical students, and patients with sleep disorders were studied. Sleep disorders included OSA, periodic limb movements in sleep (PLMS), insomnia, and narcolepsy. The degree of subjective sleepiness in each group was measured by the Korean version of Epworth sleepiness scale and compared. The relationship between polysomnographic findings reflecting severity of sleep disorder in each patient group and subjective sleepiness was analyzed. As for patients with narcolepsy, the relationship between the mean sleep latency and subjective sleepiness was studied. Results: There was a significant difference of ESS score (F=68.190, dF=5.752, p<0.001) among daytime workers, medical students, and sleep disorder patients. In OSA patient group, the degree of the sleepiness had no significant correlation either with mean O2 satuaration (p=0.062) or with RDI (p=0.807). In PLMS patient group, there was no correlation between periodic limb movement index (PLMI) and subjective sleepiness (p=0.761). In narcolepsy patient group, the subjective sleepiness had no correlation with mean sleep latency measured with MSLT (p=0.055). Conclusion: We found a significant difference of subjective sleepiness among daytime workers, medical students, and patients with sleep disorders. However, no consistent correlation was found between severity of subjective sleepiness and objective polysomnographic findings reflecting severity of each sleep disorder. This research confirms that the evaluation of subjective sleepiness is important clinically, but it cannot substitute the objective measures such as nocturnal polysomnography and MSLT.