• Title/Summary/Keyword: Frequently used keywords

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Research Trends of Korean Journalism and Communication Studies Using a Semantic Network Analysis (언어 네트워크 분석을 통해 살펴본 한국 언론학 분야 연구의 연구동향 분석)

  • Lee, Sungjoon
    • The Journal of the Korea Contents Association
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    • v.16 no.7
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    • pp.179-189
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    • 2016
  • This aim of this study is identify research trends and intellectual structure in the field of Korean journalism and communication studies. For this purpose, a semantic network analysis was employed to analyze keywords in the abstracts of published articles in the Korean Journal of Journalism and Communication Studies from 2005 to 2015. The results showed that "frame", "Twitter", "content analysis" and "social media" are among the most frequently used keywords in the abstracts during this period. With regards to degree and eigenvector centrality, "social capital", "trust" and "twitter" were among the highest. The findings of the periodic characteristics of research trends revealed that there are more studies that employ the traditional media effect theories including Uses and Gratification Theory, Agenda Setting Theory, and Framing Theory before the year of 2010 while those that focus on the specific new media such as smartphones and twitter after 2011. This study has implications in the sense that it can be used as guidelines for making a curriculum or establishing the research system for Korean journalism and communication studies in the future.

A Study on Analysis of the Trend of Blockchain by Key Words Network Analysis (키워드 네트워크 분석 방법을 활용한 블록체인 트렌드 분석에 관한 연구)

  • Cho, Seong-Hwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.5
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    • pp.550-555
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    • 2018
  • This study aims to identify and compare contents and keywords used in articles related to blockchain applications to various industries. The text mining and Semantic Network Analysis, as methods of keyword network analysis, were used to analyze articles including terms of 'finance' 'energy' and 'logistics', which media and government frequently mentioned as areas that can apply blockchain technologies. For this study, data were collected from 43,093 articles from January, 2017 through July, 2018. Data crawling was carried out by using Python BeautifulSoup and data cleaning was performed in order to eliminate mutual redundancies of the three terms. After that, text mining and semantic network analysis were performed using Textom and UCInet for network analysis between keywords. The results showed that all the three terms were similar in terms of 'technology', but there were differences in the contents of 'government policy' or 'industry' issues. In addition, there were differences in frequencies and centralities of these terms.

Research trends in statistics for domestic and international journal using paper abstract data (초록데이터를 활용한 국내외 통계학 분야 연구동향)

  • Yang, Jong-Hoon;Kwak, Il-Youp
    • The Korean Journal of Applied Statistics
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    • v.34 no.2
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    • pp.267-278
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    • 2021
  • As time goes by, the amount of data is increasing regardless of government, business, domestic or overseas. Accordingly, research on big data is increasing in academia. Statistics is one of the major disciplines of big data research, and it will be interesting to understand the research trend of statistics through big data in the growing number of papers in statistics. In this study, we analyzed what studies are being conducted through abstract data of statistical papers in Korea and abroad. Research trends in domestic and international were analyzed through the frequency of keyword data of the papers, and the relationship between the keywords was visualized through the Word Embedding method. In addition to the keywords selected by the authors, words that are importantly used in statistical papers selected through Textrank were also visualized. Lastly, 10 topics were investigated by applying the LDA technique to the abstract data. Through the analysis of each topic, we investigated which research topics are frequently studied and which words are used importantly.

A scientometric, bibliometric, and thematic map analysis of hydraulic calcium silicate root canal sealers

  • Anastasios Katakidis;Konstantinos Kodonas;Anastasia Fardi;Christos Gogos
    • Restorative Dentistry and Endodontics
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    • v.48 no.4
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    • pp.41.1-41.17
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    • 2023
  • Objectives: This scientometric and bibliometric analysis explored scientific publications related to hydraulic calcium silicate-based (HCSB) sealers used in endodontology, aiming to describe basic bibliometric indicators and analyze current research trends. Materials and Methods: A comprehensive search was conducted in Web of Science and Scopus using specific HCSB sealer and general endodontic-related terms. Basic research parameters were collected, including publication year, authorship, countries, institutions, journals, level of evidence, study design and topic of interest, title terms, author keywords, citation counts, and density. Results: In total, 498 articles published in 136 journals were retrieved for the period 2008-2023. Brazil was the leading country, and the universities of Bologna in Italy and Sao Paolo in Brazil were represented equally as leading institutions. The most frequently occurring keywords were "calcium silicate," "root canal sealer MTA-Fillapex," and "biocompatibility," while title terms such as "calcium," "sealers," "root," "canal," "silicate based," and "endodontic" occurred most often. According to the thematic map analysis, "solubility" appeared as a basic theme of concentrated research interest, and "single-cone technique" was identified as an emerging, inadequately developed theme. The co-occurrence analysis revealed 4 major clusters centered on sealers' biological and physicochemical properties, obturation techniques, retreatability, and adhesion. Conclusions: This analysis presents bibliographic features and outlines changing trends in HCSB sealer research. The research output is dominated by basic science articles scrutinizing the biological and specific physicochemical properties of commonly used HCSB sealers. Future research needs to be guided by studies with a high level of evidence that utilize innovative, sophisticated technologies.

Analysis of YouTube Viewers' Characteristics and Responses to Virtual Idols (버추얼 아이돌에 대한 유튜브 시청자 특성과 반응 분석)

  • JeongYoon Kang;Choonsung Shin;Hieyong Jeong
    • Journal of Information Technology Services
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    • v.23 no.3
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    • pp.103-118
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    • 2024
  • Due to the advancement of virtual reality technology, virtual idols are widely used in industrial and cultural content industries. However, it is difficult to utilize virtual idols' social perceptions because they are not properly understood. Therefore, this paper collected and analyzed YouTube comments to identify differences about social perception through comparative analysis between virtual idols and general idols. The dataset was constructed by crawling comments from music videos with more than 10 million views of virtual idols and more than 10,000 comments. Keyword frequency and TF-IDF values were derived from the collected dataset, and the connection centrality CONCOR cluster was analyzed with a semantic network using the UCINET program. As a result of the analysis, it was found that virtual idols frequently used keywords such as "person," "quality," "character," "reality," "animation," while reactions and perceptions were derived from general idols. Based on the results of this analysis, it was found that while general idols are mainly evaluated with their appearance and cultural factors, social perceptions of virtual idols' values are mixed with evaluations of cultural factors such as "song," "voice," and "choreography," focusing on technical factors such as "people," "quality," "character," and "animation." However, keywords such as "song," "voice," "choreography," and "music" are included in the top 30 like regular idols and appear in the same cluster, suggesting that virtual idols are gradually shifting away from minority tastes to mainstream culture. This study aims to provide academic and practical implications for the future expansion of the industry and cultural content industry of virtual idols by grasping the social perception of virtual idols.

A Review of Recent Acupuncture Therapy for Polycystic Ovarian Syndrome (다낭성 난소 증후군에 대한 침치료 연구 동향)

  • Cho, Hye-Sook;Lee, In-Sun
    • Korean Journal of Acupuncture
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    • v.28 no.3
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    • pp.165-175
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    • 2011
  • Objectives : The purpose of this study is to review and summarize the research on Polycystic ovarian syndrome (PCOS). Methods : We searched the clinical studies with keywords of Polycystic ovarian syndrome and acupuncture therapy through the search site called CAJ (china academic journal) from 2000 to 2011. Results and Conclusions : We reviewed 22 studies about PCOS which were relative to acupuncture therapy. We investigated the frequency of Acupuncture point for PCOS in this article exclusive Auricular acupuncture treatment. SP6 (Sam$\={u}$mgyo), CV4 (Kwanwon), CA111 (Chagung), SP10 (Hy$\={o}$lhae), CV6 (Kihae), B23 (Shinsu) and S40 (P'ungnyung) were used frequently. Acupuncture therapy was effective method to improve Polycystic ovarian syndrome. Further studies needed for Polycystic ovarian syndrome.

Research in Shopping: Review of Academic Disciplines for a Shopping Theory (쇼핑연구 고찰: 학술영역 이해를 통한 쇼핑이론의 기초적 접근)

  • Park, Kyung-Ae
    • Journal of the Korean Society of Clothing and Textiles
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    • v.32 no.11
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    • pp.1802-1813
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    • 2008
  • As a very first step for theorizing shopping, this study attempted to diagnose the current of shopping research. Using the keyword of shopping from major academic databases in Korea, the study collected 560 research articles and analyzed patterns of: 1) research by year, journal, and academic area; 2) researchers by academic area; 3) keywords; and 4) research contents. Analyses showed that two thirds of articles in shopping were published after 2000. While the number of journals was the highest in business and engineering, the numbers of articles and researchers were the highest in business and apparel. The most frequently used included internet shopping mall, internet shopping, and shopping orientation. About 66% of shopping research was internet shopping related, and 80% was empirical study using individual consumers. Though shopping was studied as an individual consumer behavior, there were noticeable patterns in research contents by academic field. The study discussed such patterns and provided implications for multidisciplinary approaches for shopping theory and research.

Meta Analysis on the Trade Settlement Study and Research Outlook (무역결제 분야 연구의 메타분석과 전망)

  • Hee-Jung Yeo
    • Korea Trade Review
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    • v.46 no.2
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    • pp.371-387
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    • 2021
  • This paper analyzed 110 papers related to the field of trade settlement published in the Korea Trade Review for 40 years from 1980 to 2019. This study tried to provide an insight on research topics and to suggest future research directions. The papers were analyzed according to the detailed topics of trade settlement. Research trends were identified every ten years by investigating the most frequently used titles and keywords. The analysis found that the direction of the research changed in line with the changes in trade settlement practices. Future research lies in the field of electronicization of traditional settlement methods, search for alternative settlement methods, individual international microtransaction and trade fraud.

A Study on Differences of Contents and Tones of Arguments among Newspapers Using Text Mining Analysis (텍스트 마이닝을 활용한 신문사에 따른 내용 및 논조 차이점 분석)

  • Kam, Miah;Song, Min
    • 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.

A Review on Clinical Research Trends in the Treatment on Narcolepsy in Traditional Chinese Medicine (기면증 치료에 대한 중의학 임상연구 동향)

  • Hong, Min-Ho;Koo, Byung-Su;Kim, Geun-Woo
    • Journal of Oriental Neuropsychiatry
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    • v.31 no.1
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    • pp.39-47
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    • 2020
  • Objectives: The purpose of this study was to review the research trends in the treatment on narcolepsy in traditional Chinese medicine. Methods: We searched articles in the China National Knowledge Infrastructure (CNKI) October 2009-September 2019. Keywords were 发作性睡病, 嗜睡病, and 嗜睡症. Results: Among a total of 81 articles, 12 articles were selected. The International Classification of Sleep Disorders was most frequently used as a diagnostic criteria. Feng Chi (GB20) and Baek Hoi (GV20) are the most commonly used acupoints in acupuncture treatment. Glycyrrhizae Radix (甘草), Atractylodis Rhizoma Alba (白朮), and Poria (Hoelen) (茯苓) are the most commonly used preparations in herbal medicine. The effective rate is most commonly used as an outcome measurement. Conclusions: Acupuncture and herbal medicine could be considered to improve the symptoms of narcolepsy. In the future, this study could be primary data for the development of more clinical research on the treatment on narcolepsy in Korean medicine.