• 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.15
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• pp.329-353
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• 2008

Tasan Jeong Yak-yong is great scholar, who makes a synthesis of Sil-hak[實學, Practical Science of Korea], reformer of society, and a poet in the Joseon Dynasty. He expressed contradiction and conflict of those days by intellectual language, and reperceived basic ideology of the Joseon society. Also he theorized dissatisfaction of the people about those days and its system as form of religion. We can divide Tasan's life into two times. The first part is his ages 16~39 in the period of Jeong-jo(1777~1800). The second part is in the period of Sun-jo(1801~1834). In this period, he was exiled into Gang-jin for 17 years. After banishment, he lived a quiet life for the rest of his life in his hometown. His allegoric poetry were written in this second period. The special feature of allegoric poetry is strong satire. An allegory would be that is 'king's ear', which the barber has sight, or the barber's voice, which has divulged king's secret among the bamboos. Otherwise it would be that is the sound 'king's ear is donkey's ear' in the bamboos. This sound is divulging of the true donkey's ear. It doesn't travel to audiences, but travels trough wind in the bamboos. The narration exists just as story that barber can't stand to keep silence about king's secret. There are exposure of true and critical motive as allegoric expression. Tasan's allegoric poetry stand on the basis of his love for the people. Also there reveals his thought deeply with an enormous amount of reading and self-communion. Moreover there are his warm mind with his sharp insight in which captures alive lives as allegoric materials. Most of allegoric poetry satirize actuality of those days to make an excuse for external distinguishing marks of animals and plants. However Tasan's poetry are different from them. After he grasped serious problems from his contemporary actuality, and then choosed allegoric media to express correctly. Because he grasped the special features of lives after minute observation, he could exposure controversial point of the actual. His sharp insight was not limited to allegoric media. He noticed his period and the current of his society sensitively. It made his allegoric poetry as important materials to make us to know the condition of the people in the Joseon Dynasty. Tasan's allegoric poetry is inherited by Baek Seok[白石, 1912~1995] as regular juvenile literature. Baek Seok's juvenile stories are the results of expansion and transition for Tasan's allegoric poetry. Allegoric poetry was the shout of barber to prosecute about social irregularities and contradiction, and the sound of the bamboos to travel moaning of the people in the past. Now allegoric poetry create new emotion to make us to speculate ourselves with our surrounding. This changes are caused by special feature of allegoric poetry as a form to reflect our general lives.

• The Journal of Korean Philosophical History
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• no.23
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• pp.155-180
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• 2008

Suam(遂庵) Kwon Sang-Ha(權尙夏) was a very important character in the late Chosoen Dynasty. He was a representative of the academic circles(school of Uam) and political circles(Nolon; 老論) after Uam(尤庵) Song Si-Yeol(宋時烈, 1607-1689). He represented learning and thought and undertaking of his academic circles and political circles, and handed down to his pupils. He thought his mission was "lighting the laws of heaven and aligning the human mind," "stopping the heretical study and repulsing uncivilization", to reform good virtues of humanity and justice. Kwon Sang-Ha was a successor of Song Si-Yeol, He succeeded learning and thought of his teacher and practiced "Upright"(直) and the Thought of ChunChu(春秋). He emphasized "Upright" as a fundamental principle, like his teacher. He thought ChuHsi(朱熹, 1130-1200) was the master who had inherited the spirit of Confucianism and Chosoen was the only country to successfully inherit this spirit of Confucianism. He declared any study counter to the study of ChuHsi as a rebellious pursuit. Therefore he rejected all other studies. He tried to "stop the heretical 'ism' and repulse uncivilization" and present this ideology as 'the Right way of Human Society(世道)'. He made efforts to reorganize books of ChuHsi to make perfect Book of righteousness with Song Si-Yeol. And he established Hwayang shrine, MandongMyo(萬東廟), Deabodan(大報壇) etc, in memory of fidelity and large rightness. Kwon Sang-Ha did these undertaking to establish 'Public morals and the Right way of Human Society(世道)' with self-confidence. In Dispute on the nature of man and animal(人物性同異論), he gives his approval to Han Won-Jin's opinion. Han Won-Jin's opinion was "the nature of man and animal is Different"(人物性異論). Whenever serious political accidents occurred, he took the lead to protect his teacher, Song Si-Yeol. The reason he did this was not because of his personal feelings for his teacher, but because of promoting 'Public morals(世道)' and 'Confucianism.' Kwon Sang-Ha regarded Mind control Law of "Upright" and the thought of ChunChu as his moralities, and was concerned about real politics and opposed social irregularities. Kwon Sang-Ha succeeded Song Si-Yeol's thought of "Upright" and volition of making an inroad on the Chung(淸), and gave to his political circles(Nolon; 老論) as a law of mind and mission.