• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.845-854
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• 2016

Sentiment analysis or opinion mining is a technique of text mining employed to identify subjective information or opinions of an individual from documents in blogs, reviews, articles, or social networks. In the literature, only a problem of binary classification of ratings based on review texts in an online review. However, because there can be positive or negative reviews as well as neutral reviews, a multi-class classification will be more appropriate than the binary classification. To this end, we consider the multi-class classification of ratings based on review texts. In the preprocessing stage, we extract words related with ratings using chi-square statistic. Then the extracted words are used as input variables to multi-class classifiers such as support vector machines and proportional odds model to compare their predictive performances.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.365-372
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• 2021

The purpose of this study was to examine the statements characteristics of the pressure ulcer nursing record by natural langage processing and assess the prediction accuracy for each pressure ulcer stage. Nursing records related to pressure ulcer were analyzed using descriptive statistics, and word cloud generators (http://wordcloud.kr) were used to examine the characteristics of words in the pressure ulcer prevention nursing records. The accuracy ratio for the pressure ulcer stage was calculated using deep learning. As a result of the study, the second stage and the deep tissue injury suspected were 23.1% and 23.0%, respectively, and the most frequent key words were erythema, blisters, bark, area, and size. The stages with high prediction accuracy were in the order of stage 0, deep tissue injury suspected, and stage 2. These results suggest that it can be developed as a clinical decision support system available to practice for nurses at the pressure ulcer prevention care.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.109-119
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• 2019

The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.423-429
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• 2022

This study is a study on the perceptions of pre-primary early childhood teachers on teaching and learning methods for infants and toddlers in the early childhood teacher training process. This is a mixed study using word cloud analysis and qualitative case analysis on the subject, focusing on literature research and understanding of pre-primary early childhood teachers' 'teaching and learning methods for infants and toddlers'. The purpose of this study was to find out the meaning of a early childhood teacher through thoughts on teaching and learning methods for infants, difficulties, points to be learned, teaching competency to be good as a teacher, and experiences for teaching professionalism. Through the results of this study, it is expected to find a way to increase their sense of efficacy on teaching and learning methods when conducting classes for young children in the future, and to provide basic data for improving the quality of early childhood education.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.179-197
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• 2020

This study analyzed the trends in home economics education research using the language network analysis method, focusing on papers published in the KCI list for 20 years from 2000 to 2019. A total of 501 home economics education papers analyzed through word cloud, centrality analysis, and topic modeling using NetMiner 4.4, and the results are as follows. First, the number of papers in home economics education published in the KCI listing increased gradually to 186 in the 2000s and 315 in the 2010s. The academic journals in which home economics education papers were published have been diversified to 16 in the 2000s and 22 in the 2010s. 60% of all papers were published in the 'Journal of Korean Home Economics Education Association', and since 2018, the number of papers published in the 'Journal of Learner-Centered Curriculum and Instruction' has increased dramatically. Second, in the 2000s and 2010s, home economics education studies published in KCI were categorized into home economics education content analysis, home economics educational program development & application, curriculum analysis, perception survey & direction exploration. In the 2000s, 'Home Economics Teacher' appeared as the main keyword, and a lot of perception survey & direction exploration were conducted. Relatively, the influence of 'development' increased in the 2010s, and many studies were conducted to analyze home economics education contents and develop and apply home economics programs. This study has significance in that it analyzed the research trend of HEE by expanding the analysis target and analysis period of the existing studies.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.208-223
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• 2020

In the 21st general election held in April 15, 2020, the importance of social media as an election campaigning tool became more prominent when engaged with Corona 19. Therefore, in this study, various studies were conducted to establish SNS strategy as an election campaign tool. This study analyzed the contents of SNS (Facebook, Twitter, YouTube) activities as an election campaign tool to analyze messages on social media messages of candidates Lee Nak-yeon and candidate Hwang Kyo-an of Jongno-gu, Seoul during the 2020 21st National Assembly election. Data collection mainly analyzed posts from each candidate's official account, and the research method used text analysis using the R program. Word cloud, comparative analysis, q-graph analysis, LDA, and STM analysis were used during text analysis. In addition, the analysis result was confirmed to be statistically significant through correlation analysis. As a result of research, candidate Lee Nak-yeon's election includes corona, people, problems, crisis, suffering, and wisdom, which indicates that the crisis caused by corona must be overcome through any means possible. On the other hand, candidate Hwang Kyo-an's election includes Moon Jae-in, the regime, save, the fatherland, the judge, and the economy. And from the perspective of political publicity, candidate Lee Nak-yeon made a lot of acclaims, while candidate Hwang Kyo-an made a lot of attacks, and both themes emphasized the policy rather than the image.

• Journal of Practical Agriculture & Fisheries Research
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• v.21 no.2
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• pp.103-114
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• 2019

In this study we examined the preferences of college life factors for students at Korea National College of Agriculture and Fisheries(KNCAF). Analytical techniques of unstructured data used opinion mining and text mining techniques, and the results of text mining were visualized as word cloud. And those results were used for statistical analysis of the students' willingness to farm after graduation. The items of the favorable survey consisted of 10 items in 5 areas including university image, self-capacity, dormitory, education system, and future vision. After classifying the emotions of positive and negative in the collected questionnaire, a dictionary of positive and negative was created to evaluate the preference. The items of 'college image' at the time of university support, 'self after 10 years' after graduation, 'self-capacity' and 'present KNCAF' showed high positive emotion. On the other hand, positive emotion was low in the items of 'college dormitory', 'educational course', 'long-term field practice' and 'future of Korean agriculture'. In the cross-analysis of the difference in the will to farming according to gender, farming base, and entrance motivation, the will to farm according to gender and entrance motivation showed statistically significant results, but it was not significant in farming base. Also in binary logistic regression analysis on the will to farming, the statistically significant variable was found to be 'motivation for admission'

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.119-133
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• 2020

Recently, as famous YouTubers produce and broadcast videos that receive sponsorship and advertising such as indirect advertising (PPL), a so-called 'back advertising' controversy continues, and not only famous YouTubers but also entertainers are caught up in the issue. It is causing confusion among the public in Korea. This study attempts to find out the public's reaction before and after the controversy of 'back advertising' by YouTubers through comment analysis. Specifically, among text analysis using R programs, we intend to analyze the issue through various methods such as word cloud, qgraph analysis, LDA, and word2vec analysis, a deep learning technique. The target of the analysis was to analyze the channels of three YouTubers who belonged to the controversy of the 'back advertising' YouTuber and uploaded the 'Apology video'. The 5 most recent videos of Muk-bang YouTuber Moon Bok-hee, who has a similar content disposition to SussTV's Han Hye-yeon stylist, which was controversial, and Yang Pang, a YouTuber who showed various contents (August 09, 2020) Criterion and her first 5 videos uploaded were reviewed. As a result of the study, most of the comments that showed positive reactions before the controversy, but after the controversy, it was found that negative reactions accounted for most of the comments. Therefore, this study examines the degree of change of the public about influencers through comments after the controversy over 'back advertising' through various analysis using R program. This research also devises various measures to prevent the occurrence of back advertising of influencers in the future.

• Journal of the Korean Regional Science Association
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• v.32 no.3
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• pp.29-43
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• 2016

The purpose of this study is to derive research subject that has been overlooked in previous studies and contribute to seek to the direction of research in rural development by analyzing the studies in the last 30 years on rural society. In this study, Social Network Analysis was used for identifying the changes in research themes and connection structure of keyword. The study shows that in the previous Roh Moo-Hyun's Administration from 1986 to 2000, the convergence of the research is not active. In terms of the connection structure of keyword, lots of keywords are connected to the 'Migration, IMF, Satisfaction, Green Tourism' but its form is not complicated. In the Roh Moo-Hyun's Administration from 2001 to 2007, the academic exchanges and convergence of keywords on rural development were promoted research. The connection structure of keyword was formed like a complex cluster associated with 'The Rural Elderly, Rural Tourism, Rural Development Policy, Urban-Rural Comparison'. Although some scholars who study 'Women's Studies, Tourism' formed the cluster, its form is still passive. Since 2008 until now, the keyword network of rural development research clustered densely and formed singly. It reveals that the convergence of research subjects has proceeded actively. And studies such as the 'Community, Participation, Social capital, Quality of life, Social networks, Alternative food movement' have begun.

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.504-517
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• 2018

The purpose of this study is to analyze the trends and contents of the research related to young children safety published in the domestic KCI and the candidate journals from 2010 to 2017. To analyze this, we selected 75 articles related to safety for young children published in the KCI and candidate journals from 2010 to 2017. A total of 75 papers were analyzed for frequency, percentage and ${\chi}^2$ using the SPSS Win 23.0 program. The main results of this study are as follows: First, the articles related to young children safety were published the most in 2016 and 2017 and related to infant safety were the least. Next, more than half of the research methods were conducted by quantitative research methods. The results of this study are meaningful in that it presents the necessity of safety education by analyzing trends and contents of research related to young children safety in situations where safety accidents for young children are frequent and the importance of young children safety is more emphasized. It is expected that this research will provide basic data on research topics such as disaster safety who need further research.