• 제목/요약/키워드: Word Cloud Analysis

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An Analysis of Defects Apartment Houses Occurring during the Term of Warranty Liability (하자담보책임기간에 발생하는 공동주택 하자 분석)

  • Yu, Byong-Jae;Bang, Hong-Soon;Kim, Ok-Kyue
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 한국건축시공학회 2022년도 가을 학술논문 발표대회
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    • pp.135-136
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    • 2022
  • Defects caused by apartment houses have the term of warranty liability according to the enforcement ordinance of Acts of the Management of Apartment Houses. In case when defects occur during the term, free defect maintenance can be provided from the construction company. Yet, there occur conflicts between the construction company and residents, as to whether there occur defects or not. To resolve these conflicts, this study aimed to analyze construction classification and types that need managing, based on defects of apartment houses occurring during the term of warranty liability. This research analyzed 138,576 cases of data, as of five apartment house complexes. For the construction classification for defects of apartment houses, wooden flooring products accounted for the highest rate, followed by paper hanging, and wooden window. For the construction types of defects, torn/scratching took up with the highest rate, followed by the condition of defect in fixing and operating. In order to embody defects occurring during the term of warranty liability, into the visualization technique, this researcher utilized the word cloud method. This study will pursue the method for maintaining defects during the term of warranty liability, in the subsequent research, using the data that this research presented.

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Content Analysis of Food and Nutrition unit in Middle School Textbooks of Home Economics - Focus on the National Curriculums from 1st to 2009 revised (중학교 가정(기술·가정)교과 식생활 영역의 핵심 교육내용 분석 - 제1차 교육과정부터 2009개정 교육과정의 교과서 내용을 중심으로 -)

  • Jang, Yoon-Mi;Kim, Yoo Kyeong
    • Journal of Korean Home Economics Education Association
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    • 제30권4호
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    • pp.93-112
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    • 2018
  • We analysed the textbooks of Home Economics in middle school from 1st to 2009 curriculums to investigate the contents and the portion of Food and Nutrition section. The key words were generated by word cloud technique using text-mining, and the portion of Food and Nutrition section was presented as a ratio of the pages. The core key words of Food and Nutrition section through the curriculums were 'raw food'·'food'·'diet'. In 1st and 2nd curriculums, the main key words were related to food materials, condiments and nutrients such as 'vitamin'·'protein'. The words such as 'nutrition'·'eating'·'requirement' were newly appeared in 3rd, 'portion' in 6th, and 'diet'·'adolescence' in 7th curriculum. The mean ratio of Food and Nutrition section in Home Economics was 24.3%. While the portion was as high as 31.8% in 7th it was strikingly reduced to 15.2% in 2009th. curriculum. Besides, Food and Nutrition section was composed of 10 units of middle level category during the 2nd and 3rd curriculums, and was reduced to 2 small units with none of middle level category in 2009th curriculum. Although the contents of Food and Nutrition section has been developed and adapted to the needs of the society through the curriculums, the portion of Food and Nutrition section in Home Economics has been reduced especially in 2009th curriculum, which could raise concerns on the health of individuals and communities.

Strategies for the Development of Watermelon Industry Using Unstructured Big Data Analysis

  • LEE, Seung-In;SON, Chansoo;SHIM, Joonyong;LEE, Hyerim;LEE, Hye-Jin;CHO, Yongbeen
    • The Journal of Industrial Distribution & Business
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    • 제12권1호
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    • pp.47-62
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    • 2021
  • Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.

Exploratory Big Data Analysis of Albert Camus's La Peste in Post Corona era (포스트 코로나 시대 알베르 카뮈의 『페스트』에 관한 탐색적 빅데이터 분석)

  • MIN, Jinyoung
    • The Journal of the Convergence on Culture Technology
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    • 제7권1호
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    • pp.432-438
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    • 2021
  • This dissertation's object is to confirm the drastic popularity of La Peste of Albert Camus in Korea post-corona society using big data as the mean of inductive research. Analyzing news articles concerning Camus and investigating word frequency of the book La Peste will affirm the implications La Peste has on current Korea society as the outbreak spreads. As an analysis tool, Bigkinds of Korea Press Foundation and Nuagedemots, the French version of Word Cloud were used. For the past 30 years, Albert Camus has been known in Korea as the writer of L'étranger, but after the epidemic, he earned more reputation with La Peste. Compared to L'étranger that rebelled against the world's absurdity with ennui, La peste emphasizes the importance of resistance accompanied by solidarity. La peste conveys hope by depicting disastrous situations of citizens who confront the plague by organizing a health college. The novel delivers a lot of ethical inspiration to humanity in this exceptional circumstance of COVID-19.

Interpretation of the Forest Therapy Process and Effect Verification through KeyWord Analysis of Literature on Forest Therapy (산림치유 효과 검증 연구의 주요어 분석을 통한 치유 발현과정 해석)

  • Park, Kyeong-Ja;Shin, Chang-Seob;Kim, Dongsoo
    • Journal of Korean Society of Forest Science
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    • 제110권1호
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    • pp.82-90
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    • 2021
  • In this study, the validity of the forest therapy process, in which forest activities using forest therapy factors lead to immunity promotion and health promotion, was analyzed theoretically and qualitatively to refine and systemize the forest therapy concept. Research and analysis data were collected from the websites of institutions related to forest therapy; 33 theses and 33 original research articles from 2000 to March 2020 were searched for forest therapy key words, as well as the prize winning work of the 2016 forest therapy experience essay. A word cloud was generated by frequency of nouns and adjectives and from the key words in the web pages, theses, articles, and the forest therapy experience essay. Through interpretation of word frequency, the systemic flow of forest therapy was defined. The results suggest that the source of forest therapy's power was a positive experience of the forest and an improved attitude toward nature as well as forest therapeutic factors. The therapeutic effect is maximized through the forest healing program, leading to physical and mental resilience and resistance; consequently, health and immunity are promoted. From this study, forest therapy is proposed as "a health promotion activity for the psychological, physical, and spiritual resilience of the subjects through various environmental factors of the forest, positive experiences, and attitudes toward the forest."

A Study on the Perception of Fashion Platforms and Fashion Smart Factories using Big Data Analysis (빅데이터 분석을 이용한 패션 플랫폼과 패션 스마트 팩토리에 대한 인식 연구)

  • Song, Eun-young
    • Fashion & Textile Research Journal
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    • 제23권6호
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    • pp.799-809
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    • 2021
  • This study aimed to grasp the perceptions and trends in fashion platforms and fashion smart factories using big data analysis. As a research method, big data analysis, fashion platform, and smart factory were identified through literature and prior studies, and text mining analysis and network analysis were performed after collecting text from the web environment between April 2019 and April 2021. After data purification with Textom, the words of fashion platform (1,0591 pieces) and fashion smart factory (9750 pieces) were used for analysis. Key words were derived, the frequency of appearance was calculated, and the results were visualized in word cloud and N-gram. The top 70 words by frequency of appearance were used to generate a matrix, structural equivalence analysis was performed, and the results were displayed using network visualization and dendrograms. The collected data revealed that smart factory had high social issues, but consumer interest and academic research were insufficient, and the amount and frequency of related words on the fashion platform were both high. As a result of structural equalization analysis, it was found that fashion platforms with strong connectivity between clusters are creating new competitiveness with service platforms that add sharing, manufacturing, and curation functions, and fashion smart factories can expect future value to grow together, according to digital technology innovation and platforms. This study can serve as a foundation for future research topics related to fashion platforms and smart factories.

Research on the change of perception of abandoned dogs through big data analysis

  • Jang, Ji-Yun;Lee, Seok-Won
    • Journal of the Korea Society of Computer and Information
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    • 제26권9호
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    • pp.115-123
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    • 2021
  • This study aims to analyze the changes in public perception of abandoned dogs through big data analysis. Data from January 2017 to July 2020 were collected to analyze how the quantitative change in social issues with abandoned dogs as a keyword had an effect on public perception of abandoned dogs, and factors that influence positive/negative perceptions. As a result of the study, it was confirmed that the number of stray dogs and the number of documents related to stray dogs had a positive correlation, and specific time series changes were found through various analysis techniques such as text mining, network analysis, and sentiment analysis. This study will have significance as basic data that can be used for policy establishment or other research on abandoned dogs. we hope it will help to solve problems so as to improve awareness of abandoned dogs and develop a sense of responsibility.

Arab Spring Effects on Meanings for Islamist Web Terms and on Web Hyperlink Networks among Muslim-Majority Nations: A Naturalistic Field Experiment

  • Danowski, James A.;Park, Han Woo
    • Journal of Contemporary Eastern Asia
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    • 제13권2호
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    • pp.15-39
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    • 2014
  • This research conducted a before/after naturalistic field experiment, with the early Arab Spring as the treatment. Compared to before the early Arab Spring, after the observation period the associations became stronger among the Web terms: 'Jihad, Sharia, innovation, democracy and civil society.' The Western concept of civil society transformed into a central Islamist ideological component. At another level, the inter-nation network based on Jihad-weighted Web hyperlinks between pairs of 46 Muslim Majority (MM) nations found Iran in one of the top two positions of flow betweenness centrality, a measure of network power, both before and after early Arab Spring. In contrast, Somalia, UAE, Egypt, Libya, and Sudan increased most in network flow betweenness centrality. The MM 'Jihad'-centric word co-occurrence network more than tripled in size, and the semantic structure more became entropic. This media "cloud" perhaps billowed as Islamist groups changed their material-level relationships and the corresponding media representations of Jihad among them changed after early Arab Spring. Future research could investigate various rival explanations for this naturalistic field experiment's findings.

Sentiment Analysis of the Quotations of Intensive Care Unit Survivors in Qualitative Studies (질적연구 진술문을 이용한 중환자실 생존자의 감성분석)

  • Kang, Jiyeon
    • Journal of Korean Critical Care Nursing
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    • 제11권1호
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    • pp.1-14
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    • 2018
  • Purpose : As the intensive care unit (ICU) survival rate increases, interest in the lives of ICU survivors has also been increasing. The purpose of this study was to identify the sentiment of ICU survivors. Method : The author analyzed the quotations from previous qualitative studies related to ICU survivors; a total of 1,074 sentences comprising 429 quotations from 25 relevant studies were analyzed. A word cloud created in the R program was utilized to identify the most frequent adjectives used, and sentiment and emotional scores were calculated using the Artificial Intelligence (AI) program. Results : The 10 adjectives that appeared the most in the quotations were 'difficult', 'different', 'normal', 'able', 'hard', 'bad', 'ill', 'better', 'weak', and 'afraid', in order of decreasing occurrence. The mean sentiment score was negative ($-.31{\pm}.23$), and the three emotions with the highest score were 'sadness'($.52{\pm}.13$), 'joy'($.35{\pm}.22$), and 'fear'($.30{\pm}.25$). Conclusion : The natural language processing of AI used in this study is a relatively new method. As such, it is necessary to refine the methodology through repeated research in various nursing fields. In addition, further studies on nursing interventions that improve the coherency of ICU memory of survivors and familial support for the ICU survivors are needed.

Comparison of Public and Private Perspectives on Central Bank CBDC - Focusing on Korean Case (중앙은행 CBDC에 대한 공공 및 민간 관점의 인식 비교연구- 한국 사례를 중심으로)

  • Kim, Bong-Kyu;Lee, Won-Boo
    • The Journal of the Korea Contents Association
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    • 제21권9호
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    • pp.360-371
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    • 2021
  • The advent of virtual currencies has heightened interest in the Central Bank Digital Currency (CBDC) issued by the central bank. Recently, central banks in some countries have already decided to issue CBDCs or are in the test phase. This study will be an opportunity to compare public and private perceptions of central banks and explore various issues related to the introduction of CBDCs in the future through analysis methods of big data.