• Korean Journal of Culture and Social Issue
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• v.10 no.3
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• pp.103-129
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• 2004

This article examines the Korean adolescents and adults' social representation and trust of Korean society and people using indigenous psychological analysis. Respondents were asked to write in an open-ended questionnaire their perception of the following five aspects: Korean politics, economy, society, culture and people. They were then asked to report why they trust or distrust Korean society. A total of 1,064 respondents (218 middle school students, 200 university students, 218 fathers of the middle school students, 218 mothers of the middle school students, and 210 teachers) completed a questionnaire developed by the present researchers. The data were collected during April to June, 2003. The results indicate that 94.5% of Koreans view the existing political system and politicians as being corrupt, inept, factional, and lacking in integrity. A vast majority (84.9%) recognize the existence of systemic problems in the Korean economy. A total of 78.2% see problems in Korean society being dominated by selfishness, factionalism, conservatism, and social uncertainty. For Korean culture, a majority of respondents report being proud of its cultural tradition, accomplishment, and creativity. At the same time, 45.7% report loss of cultural identity and pride due to external influences. More than half of the respondents report negative aspects of Korean people (i.e., selfish, lack of morality, rushed, and overly focused on their social image), while nearly half of the respondents report positive aspects of Korean people as being compassionate, cooperative, good-natured and hard-working. As for reason for trusting Korean society, around a third report "because it is our country," followed by its future potential, and the good-nature and willingness of Korean people to work hard. The reasons for distrusting Korean society is the dishonesty politicians, corruption, institutional ineptness, and economic uncertainty. These results indicate a low level of collective efficacy in influencing and affecting change in Korean society.

• Korean Journal of Culture and Social Issue
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• v.8 no.1
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• pp.103-139
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• 2002

Korean society has significantly changed with the onset of a dramatic economic crisis in 1998. From 2000, however, the Korean economy has recovered and currently Korea is enjoying a similar standard of living and economic growth as the pre-1998 levels. This study is a follow-up analysis, comparing the results examining the success attribution of Korean students and adults in 2001 with the results obtained before the economic crisis in 1997. Using the indigenous psychological approach, this study compares the similarities and differences in Korean students and adults' attribution of their personal success before and after the economic crisis. A total of 988 participants, consisting of 481 primary, junior high, senior high and university students and 507 adults (236 fathers and 271 mothers of the students) completed the questionnaire developed by Kim and Park (1998). The results indicate that students perceived their academic achievement and adults perceived successful family life as their most proud achievement. Successful family life included items such as academic success of children, healthy development of their children, and harmonious family life. The person who provided the most significant support for students were parents and for adults, it was their spouse. For students, the importance of friends' social support increased during the high school years. In terms of type of social support, emotional support was reported to be the most important for both students and adults. As for the reason for their success, majority of students and men reported self-regulation and for women, supportive family environment was reported as being the most important. Comparing 2001 results with the 1997 results, the importance of family increased after the economic crisis. Even with the dramatic economic crisis, however, some of the underlying pattern remain strong (such as importance of academic achievement for students, family life for adults, the importance of social support, especially emotional social support from family members, and believing that self-regulation would lead to success). The similar pattern of results obtain before and after the economic crisis indicate that the above results reflect a fundamental values and belief system deeply imbedded in Korean mentality.

• Sim-seong Yeon-gu
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• v.28 no.2
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• pp.107-138
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• 2013

The purpose of this article is to awaken our colleagues to the culture and mind issues that have been forgotten or neglected by contemporary psychiatry under the prevalence of materialistic orientation. Cultural psychiatry too, though it has been contributed a great deal to widen the mental vision of psychiatry, has revealed several limitations in its approach. In the course of one sided search for culture specific factors in relation to mental health, conventional cultural psychiatry has neglected an effort to explore the common root underlying the different cultures and the common foundation of human mind. Cross sectional comparisons of the cultures alone have inevitably prevented the global considerations to culutre and mind in historical aspects and the dynamic interactions between mind and culture more in depth. The author suggested that the total view of mind and total approach of analytical psychology of C.G. Jung might be capable to replenish those limitations. Author explained the ways of C.G. Jung's observations and experiences of non-western culture and his concepts of culture and mind. The author demonstrated Jung's view of culture with the example of Filial Piety, Hyo, the Confucian moral norm which can be regarded as components of the collective consciousness though connected with archetypal patterns of behavior of intimacy between parent and child. In regard to the coexistence of multi-religious cultures in Korea the author made a proposal of 'culture spectrum' model for understanding value orientations of person in religious cultures. He identified in case of the Korean 4 types of cultural spectrums: Person with predominantly the Buddhist culture; with the Confucian; with the Shamanist; and with the Christian culture. The author also made an attempt to depict the dynamic interactions of different religious cultures in historical perspectives of Korea. Concepts of mind from the Eastern thoughts were reviewed in comparison with Jung's view of mind. The Dao of Lao Zi, One Mind by Wonhyo, the Korean Zen master from the 7th century, the Diagram of the Heaven's Decree by Toegye, a renowned Neo-Confucianist of Korea from the 16th century and his theory of Li-Ki, were explored and came to conclusion that they represent certainly the symbol of the Self in term of C.G. Jung. The goal of healing is 'the becoming whole person'. Becoming whole person means bringing the person as an individual to live not only within the specific culture but also to live in the world beyond the culture which is deeply rooted in the primordial foundation of human mind.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.990-1010
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• 2009

To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Music and Human Behavior
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• v.5 no.1
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• pp.67-90
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• 2008

This case used MI techniques that give an imagery experience to depressed client's mental resource, and that makes in to verbalism. Also those images are supportive level therapy examples that apply to positive variation. MI is simple word of 'Music and Imagery' with one of psychology cure called GIM(Guided Imagery and Music). It makes client can through to the inner world and search, confront, discern and solve with suitable music. Supportive Level MI is only used from safety level music. Introduction of private session can associate specification feeling, subject, word or image. And those images are guide to positive experience. The First session step of MI program is a prelude that makes concrete goal like first interview. The Second step is a transition that can concretely express about client's story. The third step is induction and music listening. And it helps to associate imagery more easily by used tension relaxation. Also it can search and associate about various imagery from the music. The last step is process that process drawing imagery, talking about personal imagery experience in common with therapist that bring the power by expansion the positive experience. Client A case targets rapport forming(empathy, understanding and support), searching positive recourse(child hood, family), client's emotion and positive support. Music must be used simple tone, repetition melody, steady rhythm and organized by harmony music of what therapist and client's preference. The client used defense mechanism and couldn't control emotion by depression in 1 & 2 sessions. But the result was client A could experience about support and understanding after 3 sessions. After session 4 the client had stable, changed to positive emotion from the negative emotion and found her spontaneous. Therefore, at the session 6, the client recognized that she will have step of positive time at the future. About client B, she established rapport forming(empathy, understanding and support) and searching issues and positive recognition(child hood, family), expression and insight(present, future). The music was comfortable, organizational at the session 1 & 2, but after session 3, its development was getting bigger and the main melody changed variation with high and low of tune. Also it used the classic and romantic music. The client avoids bad personal relations to religious relationship. But at the session 1 & 2, client had supportive experience and empathy because of her favorite, supportive music. After session 3, client B recognized and face to face the present issue. But she had avoidance and face to face of ambivalence. The client B had a experience about emotion change according depression and face to face client's issues After session 4. At the session 5 & 6, client tried to have will power of healthy life and fairly attitude, train mental power and solution attitude in the future. On this wise, MI program had actuality and clients' issues solution more than GIM program. MI can solute the issue by client's based issue without approach to unconsciousness like GIM. Especially it can use variety music and listening time is shorter than GIM and structuralize. Also can express client's emotion very well. So it can use corrective and complement MI program to children, adolescent and adult.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.