• Title/Summary/Keyword: analysis of research article

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Material as a Key Element of Fashion Trend in 2010~2019 - Text Mining Analysis - (패션 트렌트(2010~2019)의 주요 요소로서 소재 - 텍스트마이닝을 통한 분석 -)

  • Jang, Namkyung;Kim, Min-Jeong
    • Fashion & Textile Research Journal
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    • v.22 no.5
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    • pp.551-560
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    • 2020
  • Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

An Analysis of Research Trends in Domestic Articles on Preschooler Peer Relationships(1995-2009) : Focusing on Research Methods (유아 또래관계 관련 국내 학술지 논문의 연구동향 분석 : 연구방법을 중심으로(1995년~2009년))

  • Kim, Youn-Hee
    • Korean Journal of Child Studies
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    • v.31 no.5
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    • pp.131-149
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    • 2010
  • The purpose of this study was to examine research trends in articles of preschooler peer relationships carried in domestic academic journals. This was done in an attempt to suggest alternative directions for peer relationship studies in the early childhood education sector and lay the foundation for future studies. 131 articles that appeared in seven domestic academic journals related to early childhood education were selected and analyzed in order to better understand the general trends in the filed and the specific trends in terms of their content and methods. Our results indicate that the observation method was most common in the quantitative studies, and participant observation was most prevailent among qualitative studies. As for instrumentation, international instruments were most widely utilized, and the most dominant analysis method was descriptive statistics. In terms of reliability, internal consistency was checked most often, however, the majority of the studies failed to provide any information on validity and post-hoc analysis.

Research Trends in Journal of Fashion Business -A Social Network Analysis of Keywords in Fashion Marketing and Design Area- (키워드 네트워크 분석을 통한 「패션비즈니스」 연구 동향 -패션마케팅 및 디자인 분야를 중심으로-)

  • Lee, MiYoung;Lee, Jungmin
    • Journal of Fashion Business
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    • v.23 no.3
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    • pp.51-66
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    • 2019
  • The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.

Literacture Review of Dental Infection Control in Korea(1988~2009) (치과 감염 관리에 관한 국내 문헌고찰(1988~2009년))

  • Choi, Ha-Na;Bae, Hyun-Sook;Cho, Young-Sik
    • Journal of dental hygiene science
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    • v.10 no.4
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    • pp.199-209
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    • 2010
  • The purpose of this paper is to suggest fundamental data for finding problems and ways to improve Korean dental infection control studies through the classification of literature on dental infection control which have been conducted in Korea. The collection of literature was done via seven online database programs only for domestic literature. The date of first search was September 16-17th, 2009, and the final search was completed on December 20th, 2009. (1) From the examination of the frequency of research according to the publishing form by year, it is revealed that after 2006, dental infection control is being performed most vigorously, compared with 1980's when the studied on this area started. (2) According to the classification of research method by research design of original article among the literature, original articles were 45 studies, and the others were 20 studies. It was also found that in 45 studies of original article, there were 37 studies of survey research, and there were 8 studies which include microbiology examination. (3) On the analysis of the subject of each study, glob and mask using rate have gradually increased, and the frequency of pierced with sharp implement or needle have gradually decreased. Through this research, it can be observed roughly how the results depended on subject of each studies change. However, it may be restricted to generalize the results of this research, because there are lack of clear standard and literature evidence to assess the interrelationship between each study. Also, since there are shortage of research and studies in dental infection control, the research to examine the effects should be tried actively after the standards and precaution of dental infection control developed.

Participation Level in Online Knowledge Sharing: Behavioral Approach on Wikipedia (온라인 지식공유의 참여정도: 위키피디아에 대한 행태적 접근)

  • Park, Hyun Jung;Lee, Hong Joo;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.97-121
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    • 2013
  • With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis (다계층 이원 네트워크를 활용한 사용자 관점의 이슈 클러스터링)

  • Kim, Jieun;Kim, Namgyu;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.93-107
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    • 2014
  • In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

A Bibliometric Analysis of Acupuncture Treatment of Osteoarthritis over the past 20 Years: 2003-2022

  • Jisu Lee;Hyonjun Chun;Sungjun Joo;Yubin Kim;Seonghyeon Jeon;Hyewon Yeum
    • Journal of Acupuncture Research
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    • v.40 no.4
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    • pp.293-307
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    • 2023
  • This study uses bibliometric methods to analyze publications regarding the use of acupuncture in osteoarthritis over the past 20 years and presents an overview of global research trends. Publications related to acupuncture in osteoarthritis from 2003 to 2022 were retrieved from the Web of Science Core Collection Database. An analysis of the extracted records was conducted according to their publication year, research area, journal title, country, organization, author, and keywords. The VOSviewer program was used to visualize the research trends on acupuncture in osteoarthritis. An analysis of 380 articles indicated a consistent increase in the use of acupuncture for osteoarthritis treatment over the past 20 years. Many articles have been published in research areas such as "integrative complementary medicine" and "general internal medicine." The most prolific journal was Evidence-Based Complementary and Alternative Medicine. In terms of article publication, the most productive country and research organization were China and the Beijing University of Chinese Medicine, respectively. The most frequently occurring keywords were "acupuncture," "knee osteoarthritis," and "pain." This study used a bibliometric analysis to provide an overview of global research trends on acupuncture in osteoarthritis. These findings may suggest the future direction of research on the treatment of acupuncture in osteoarthritis.

Analysis of Research Papers Published in the Korean Journal of Clinical Laboratory Science from 1985 to 2012

  • Koo, Bon Kyung
    • Korean Journal of Clinical Laboratory Science
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    • v.45 no.4
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    • pp.180-187
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    • 2013
  • The author surveyed and analyzed the research papers of korean journal of clinical laboratory science (KJCLS) that have been posted for 28 years from 17 volumes in 1985 to 44 volumes in 2012 in the time of 50th anniversary of foundation of the korean association of medical technologists (KAMT) of in 2012. This study is aimed to provide members with basic materials helpful to research development and suggest development measures of journal. The author analyzed the number of papers, research field, type of papers, and number of authors based on the title of paper. The total number of papers is 916 and average number of paper is 33. The research field was biochemistry 167 (18.2%), microbiology 160 (17.4%), histology & cytology 99 (10.8%), molecular genetics 77 (8.5%), hematology 69 (7.5%), physiologic function 64 (7.0%), immunology 60 (6.5%), blood bank 33 (3.6%), radioimmunoassay 33 (3.6%), parasitology 27 (2.9%), quality control 18 (2.0%), urinalysis & body fluid 13 (1.4%), cytogenetics 12 (1.3%), flow cytometry analysis 6 (0.7%), and other articles were 78 (8.5%). Regarding the type of papers, original article was 777 (84.8%), case report 52 (5.7%), review 23 (2.5%), others 64 (7.0%). Regarding the number of paper authors, single author was 208 (22.7%), 2-man joint authors 178 (19.4%), 3-man joint authors 181 (19.8%), 4-man joint authors 151 (16.5%), over-5-man joint authors 198 (21.6%). The average number of papers was 33 for 28 years from 1985 to 2012, it is fewer than number of technologists and professors working currently regardless of the level of quantity and quality. The KAMT needs paper promoting measures and strategic investment on the scholarly journals that can aggressively promote to members and inspire research desire for korea citation index (KCI) registered article selection of KJCLS in the future.

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A note for a classroom activity - Predicting German Tank Production during World War II

  • Kim G.-Daniel;Kim Sung-Sook
    • Research in Mathematical Education
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    • v.10 no.3 s.27
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    • pp.229-238
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    • 2006
  • During World War II there was a statistical analysis conducted by the Allied analysts to estimate the German war productions, including their tank productions. This article revisits the analysis of the tank productions as a classroom activity format. Various reformed ideas are proposed in order to enhance students' perspectives of the point estimation. Comprehensive simulation works and actual classroom discussions will be provided along with the theoretical investigations.

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Analysis entrepreneurship trends using keyword analysis of news article Big Data :2013~2022 (뉴스기사 빅데이터의 키워드분석을 활용한 창업 트렌드 분석:2013~2022 )

  • Jaeeog Kim;Byunghoon Jeon
    • Journal of Platform Technology
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    • v.11 no.3
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    • pp.83-97
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    • 2023
  • This research aims to identify startup trends by analyzing a large number of news articles through semantic network analysis. Using the BIGKinds article analysis service provided by the Korea Press Foundation, 330,628 news articles from 19 newspapers from January 2013 to December 2022 were comprehensively analyzed. The study focused on exploring the changes in key issues over the past decade, considering the impact of the social environment and global economic trends on entrepreneurship. We compared the number of news articles and changes in issues before and after the COVID-19 pandemic, and visualized entrepreneurship trends through frequency analysis, relationship analysis, and correlation analysis. The results of the study showed that the top keywords for entrepreneurship-related words are startup activation and commercialization, and the correlation between COVID-19 and entrepreneurship keywords is almost negligible in a linear sense, but the number of news articles decreased during the pandemic, which has an impact. In particular, the most frequently mentioned keywords are Ministry of SMEs and Startups, place is the United States, and person is limited. The agency was the SBA, and the entrepreneurship sector is more affected by social issues than any other sector, with the important characteristics of increased frequency of prompt access. This study supplies essential basic data for understanding and exploring issues and events related to entrepreneurship and suggests future research topics in the field.

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