• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.121-143
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• 2020

The present study examined the content and changes in leader role schemas associated with 'male' leaders, 'female' leaders, and 'good' leaders over the past 10 years in Korea. In addition, we analyzed how the gender of the respondents affects their perception of male leaders versus female leaders as a good leader. A total of 736 Korean adults residing in the Seoul metropolitan area participated in the survey at two different time points, one in 2007, and the other in 2017. The respondents were presented with a total of 90 behavior items driven from the literature and asked to choose the items that represent male leaders, female leaders, and good leaders, respectively. We found that the chosen behavior items for male leaders versus female leaders matched closely to the typical sex role of males (i.e., being agentic) versus females (i.e., being communal). By contrast, the chosen behavior items for good leaders reflected both the male-typed roles and the female-typed roles. We also found that the role schemas associated with male leaders as well as good leaders have changed over the 10 year period. Those schemas also differed between male versus female respondents. For female leaders, however, the role schemas were found to be stable over the 10 years. We also found that the good leader schemas are more specified and variable than are the male or the female schemas. Additionally, in the 2007 survey male characteristics overlapped with good leader characteristics to a greater degree than did female characteristics. This difference was no longer observed in the 2017 survey. The observed difference in the degree of overlap between male (versus female) characteristics with good leader characteristics was attributable to the perceptions of male respondents. We discuss implications of our findings and directions for future research.

• Korean Journal of Culture and Social Issue
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• v.26 no.2
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• pp.47-68
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• 2020

Since the early 2000s, Korea has continued to increase the proportion of the elderly population due to low fertility and increased life expectancy. As a result, Korea has now entered the aging society. Because of this demographic change, proportion of active elderly have increased, and many academics, such as sociology, economics, and psychology, have conducted various studies on the active elderly. This study focused on active elderly based on the activity theory of old age and the positive effect of small community participation activity on the elderly. The purpose of this study is to examine whether active elderly' participation in everyday activities, small community participation of the elderly affect citizen participation actively in society as a citizen, and in the process, mediates the effect of small community cohesion and the moderating effect of small community selfishness. This study performed a stepwise regression analysis and a hierarchical regression analysis of 700 elderly people who are participated actively in various small communities. As a result, the partial mediating effect of small community cohesion was shown in the relationship between participation in everyday activities and citizen participation, and the moderating effect of small community selfishness was also shown. These findings suggest that government and interested parties need to develop and implement policies for the small community participation of elderly citizens in consideration of their small community activities, small community cohesion and small community egoism.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.207-235
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• 2022

In a knowledge-based society where knowledge and information industries are the main pillars of the economy, knowledge sharing and diffusion and its systematic management are recognized as essential strategies for improving national competitiveness and sustainable social development. In the field of Information Systems (IS) research, where the convergence of information technology and management takes place in various ways, the evolution of knowledge occurs only when researchers cooperate in turning old knowledge into new knowledge from the perspective of the scientific knowledge network. In particular, it is possible to derive new insights by identifying topics of interest in the relevant research field, applied methodologies, and research trends through network-based interdisciplinary graftings such as citations, co-authorships, and keywords. In previous studies, various attempts have been made to understand the structure of the knowledge system and the research trends of the relevant community by revealing the relationship between research topics, methodologies, and co-authors. However, most studies have compared two or more journals and been limited to a certain period; hence, there is a lack of research that looked at research trends covering the entire history of IS research. Therefore, this study was conducted in the following order for all the papers (from its first issue in 1977 to the first quarter of 2022) published in the MIS Quarterly (MISQ) Journal, which plays a leading role in revealing knowledge in the IS research field: (1) After extracting keywords, (2) classifying the extracted keywords into research topics, methodologies, and theories, and (3) using topic modeling and keyword network analysis in order to identify the changes from the beginning to the present of the IS research in a chronological manner. Through this study, it is expected that by examining the changes in IS research published in MISQ, the developing patterns of IS research can be revealed, and a new research direction can be presented to IS researchers, nurturing the sustainability of future research.

• Journal of Nutrition and Health
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• v.55 no.3
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• pp.321-329
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• 2022

Riboflavin and its derivatives, flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), are key components of mitochondrial energy metabolism and oxidation-reduction reactions. Proposed dietary reference intakes for Koreans (KDRIs), that is, estimated average requirements (EARs), for riboflavin, based on current knowledge of riboflavin and riboflavin derivative levels, and glutathione reductase activity, are 1.3 mg/d for men aged 19-64 years and 1.0 mg/d for women aged 19-64 years. By applying a coefficient of variance of 10%, reference nutrient intakes (RNIs) were set at 1.5 mg/d for men aged 19-64 years and 1.2 mg/d for women aged 19-64 years. Likewise, EARs and RNIs of riboflavin intake were proposed for all age groups and women in specific life stages such as pregnancy. Mean adult riboflavin intake for adults aged ≥ 19 years was 1.69 mg/d in Korea National Health and Nutrition Examination Survey (KNHANES) 2020, which was 124.9% of EAR according to the 2020 KDRIs. In the 2015-2017 KNHANES study, the mean riboflavin intake from foods and supplements was 2.79 mg/d for all age groups, and 32.7% of individuals consumed less riboflavin than EAR according to the 2020 KDRIs. For those that used supplements, mean intakes were 1.50 mg/d for riboflavin from foods, 10.26 mg/d from supplements, and 11.76 mg/d from food and supplements, and 5.5% of individuals consumed less riboflavin than EAR. Although the upper limit of riboflavin has not been established, the merits of increasing supplement use warrant further consideration. Also, additional epidemiologic and intervention studies are required to explore the role of riboflavin in the etiology of chronic diseases.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.318-326
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• 2022

The Convention on Biodiversity (CBD) recommends that 17% of the land be designated as a protected area to counter global environmental problems. Korea also realized a need to designate protected areas according to the international level and explain the significance of designating protected areas. Accordingly, studies on ecosystem services are required. In Korea, the protected areas are designated as national parks, provincial parks, and county parks by hierarchy under the Natural Parks Act. However, as priority was on political and administrative aspects, research on ecosystem service value evaluation and habitat management were concentrated in national parks, and provincial and county parks were relatively neglected. Therefore, more studies on provincial and county parks are necessary. In this study, habitat quality for Gajisan Provincial Park, where there were few studies on habitat management and ecosystem service valuation, was evaluated using the InVEST Habitat Quality model among the InVEST models. The analysis results were compared with 16 mountainous national parks. The results showed that the habitat quality value of Gajisan Provincial Park was 0.83, higher than that of the surrounding areas. The analysis of habitat quality in three districts showed 0,84 for the Tongdosa and Naewonsa districts and 0.83 for the Seoknamsa district. By use district, the nature conservation district, the natural environment district, the cultural heritage district, and the park village district had the highest habitat quality value in that order. Compared with the existing habitat quality analysis results of national parks, Gajisan Provincial Park showed naturalness at the level of Mudeungsan National Park. These results can be used as objective data for establishing policies and management plans to preserve biodiversity and promote ecosystem services in provincial parks.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.111-129
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• 2022

Insomnia is a chronic disease in modern society, with the number of new patients increasing by more than 20% in the last 5 years. Insomnia is a serious disease that requires diagnosis and treatment because the individual and social problems that occur when there is a lack of sleep are serious and the triggers of insomnia are complex. This study collected 5,699 data from 'insomnia', a community on 'Reddit', a social media that freely expresses opinions. Based on the International Classification of Sleep Disorders ICSD-3 standard and the guidelines with the help of experts, the insomnia corpus was constructed by tagging them as insomnia tendency documents and non-insomnia tendency documents. Five deep learning language models (BERT, RoBERTa, ALBERT, ELECTRA, XLNet) were trained using the constructed insomnia corpus as training data. As a result of performance evaluation, RoBERTa showed the highest performance with an accuracy of 81.33%. In order to in-depth analysis of insomnia social data, topic modeling was performed using the newly emerged BERTopic method by supplementing the weaknesses of LDA, which is widely used in the past. As a result of the analysis, 8 subject groups ('Negative emotions', 'Advice and help and gratitude', 'Insomnia-related diseases', 'Sleeping pills', 'Exercise and eating habits', 'Physical characteristics', 'Activity characteristics', 'Environmental characteristics') could be confirmed. Users expressed negative emotions and sought help and advice from the Reddit insomnia community. In addition, they mentioned diseases related to insomnia, shared discourse on the use of sleeping pills, and expressed interest in exercise and eating habits. As insomnia-related characteristics, we found physical characteristics such as breathing, pregnancy, and heart, active characteristics such as zombies, hypnic jerk, and groggy, and environmental characteristics such as sunlight, blankets, temperature, and naps.

• Journal of The Korean Association For Science Education
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• v.42 no.3
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• pp.325-340
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• 2022

This study attempts to analyze the causes of low affective achievement of elementary, middle, and high school students in Korea in science. To this end, a total of 27 students, three to four students per grade, were interviewed by grade from the fourth grade of elementary school to the first grade of high school, and a total of nine teachers were interviewed by school level. In the interview, related questions were asked in five sub-areas of the 'Indicators of Positive Experiences about Science': 'Science Academic Emotion', 'Science-Related Self-Concept', 'Science Learning Motivation', 'Science-Related Career Aspiration', and 'Science-Related Attitude'. Interview contents were recorded, transcribed, and categorized. As a result of examining the causes of low science academic emotion, it was found that students experienced negative emotions when experiments are not carried out properly, scientific theories and terms are difficult, and recording the inquiry results is burdensome. In addition, students responded that science-related self-concept changed negatively due to poor science grades, difficult scientific terms, and a large amount of learning. The reasons for the decline in science learning motivation were the lack of awareness of relationship between science class content and daily life, difficulty in science class content, poor science grades, and lack of relevance to one's interest or career path. The main reason for the decline in science-related career aspirations was that they feel their career path was not related to science, and due to poor science performance. Science-related attitudes changed negatively due to difficulties in science classes or negative feelings about science classes, and high school students recognized the ambivalence of science on society. Based on the results of the interview, support for experiments and basic science education, improvement of elementary school supplementary textbook 'experiment & observation', development of teaching and learning materials, and provision of science-related career information were proposed.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.338-349
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• 2022

This study aims to investigate whether modular community planting, which entailed planting a variety of species of seedlings at high density, was more effective in restoring natural forests than the existing mature tree planting. We also investigated whether the planting density of the modular community planting facilitates growth or improves the tree layer coverage. We conducted outdoor experiments in which the samples were divided into a mature tree planting plot (control plot), where mature trees were planted at wide intervals, and a modular community planting (MCP) plot (treatment plot), where multiple seedlings were planted in high density. The MCP plot was further divided into the plot in which 3 seedlings were planted per m² and the plot of 1 seedling per m². We measured the specimens' survival rate, growth rate (tree height, crown width, and root collar diameter), and cover rate for 26 months from May 2019 and the predicted future tree height growth using the measured tree height. The survival rate and relative growth rate of the MCP were higher than those of the mature tree planting plot. The vertical coverage rate of the tree crown in the MCP exhibited complete coverage of the ground before 23 months, while the coverage rate of the mature tree planting decreased due to transplantation stress. The seedlings in the MCP, which were planted at high density, grew well and were predicted to grow higher than the mature trees in the large tree planting plot within 5 to 6.5 years after planting. It was due to multiple species, seedlings, high-density planting, and planting foundation improvements, such as soil enhancement and mulching. In other words, the seedlings planted in the MCP had a higher survival rate as their environmental adaptation after planting was better, and their early growth was also larger than the trees in the mature planting plot. The high-density mixed planting of various native species not only mitigated the inter-complementary environmental pressures but also facilitated growth by inducing competition between species. Moreover, the planting foundation improvement effectively increased the seedlings' viability and growth rate. A reduction in follow-up management costs is expected as the tree layer coverage sharply increases due to the higher planting density. In the MCP (3 seedlings per m² and 1 seedling per m²), the tree height growth was promoted with the higher planting density, and the crown width and root collar diameter tended to be larger with the lower planting density, but these differences were not statistically significant.