• 제목/요약/키워드: Betweenness centrality words

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연결망 분석을 활용한 우리나라 금연연구 동향분석 (A Social Network Analysis of Research Key Words Related Smoke Cessation in South Korea)

  • 안은성
    • 보건행정학회지
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    • 제29권2호
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    • pp.138-145
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    • 2019
  • Background: The purpose of this study is supposed to figure out the keyword network from 2009 to 2018 with social network analysis and provide the research data that can help the Korea government's policy making on smoking cessation. Methods: First, frequency analysis on the keyword was performed. After, in this study, I applied three classic centrality measures (degree centrality, betweenness centrality, and eigenvector centrality) with R 3.5.1. Moreover, I visualized the results as the word cloud and keyword network. Results: As a result of network analysis, 'smoking' and 'smoking cessation' were key words with high frequency, high degree centrality, and betweenness centrality. As a result of looking at trends in keyword, many study had been done on the keyword 'secondhand smoke' and 'adolescent' from 2009 to 2013, and 'cigarette graphic warning' and 'electronic cigarette' from 2014 to 2018. Conclusion: This study contributes to understand trends on smoking cessation study and seek further study with the keyword network analysis.

언어네트워크분석을 통한 국내 문화정책 연구동향 분석(2008-2017) (An Analysis of Cultural Policy-related Studies' Trend in Korea using Semantic Network Analysis(2008-2017))

  • 박양우
    • 한국콘텐츠학회논문지
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    • 제17권11호
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    • pp.371-382
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    • 2017
  • 본 연구는 콘텐츠산업정책을 포괄하는 문화정책에 대한 학술적 연구의 동향을 알고자 언어네트워크분석을 통해 국내의 가장 대표적인 문화정책 분야 전문학술지인 '문화정책논총'에 수록된 186편의 논문 주제어 832개를 대상으로 분석을 시도하였다. 시간적 범위는 한국연구재단 한국학술지인용색인 홈페이지(www.kci.go.kr)에 수록되어 있는 2008년 10월부터 2017년 1월까지로 하였다. 언어네트워크 분석은 주제어 빈도수, 밀도분석과 중심성을 지표로 분석하였으며, 이를 바탕으로 Netdraw 프로그램에 의한 시각화를 시도하였다. 언어네트워크분석 결과 가장 많은 빈도수를 기록한 주제어는 '문화'였고, '문화정책/행정', '문화산업/문화콘텐츠', '정책'이 최다의 빈도수를 기록한 그룹에 포함되었다. 빈도수가 높은 '문화정책/행정'과 '문화산업/문화콘텐츠'는 대부분의 중심성에서 우위를 차지했으나, 매개중심성은 낮아 다른 주제어들과의 중매 역할에는 한계를 드러냈다.

키워드 네트워크 분석을 활용한 치위생과학회지 연구동향 분석 (Analysis of Journal of Dental Hygiene Science Research Trends Using Keyword Network Analysis)

  • 강용주;윤선주;문경희
    • 치위생과학회지
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    • 제18권6호
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    • pp.380-388
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    • 2018
  • 본 연구는 키워드 네트워크 분석 방법을 활용하여 치위생과학회지 2001년부터 2018년 3호까지 게재된 논문 953편의 키워드를 추출하여 연구 구조를 파악하기 위해 키워드 분석과 핵심어를 파악하기 위해 중심성 분석을 실시하였다. 그리고 5년 단위로 1기를 2001년부터 2005년까지, 2기를 2006년부터 2010년까지, 3기를 2011년부터 2015년까지, 4기를 2016년부터 2018년까지로 구분하여 연구동향을 분석하여 다음과 같은 결론을 얻었다. 치위생과학회지에서 도출된 총 1,454개의 단어 중에서 17년간 치위생과학회지 투고 논문에서 가장 많이 쓰인 단어는 'Health'이며 'Dental', 'Oral', 'Hygiene', 'Hygienist'에 관한 논의가 가장 활발하였음을 알 수 있었다. 중심성 분석을 통해 치위생과학회지에서 핵심이 되는 단어들과 연결되며 중심을 형성하고 있는 단어들은 'Health', 'Dental', 'Oral', 'Hygiene', 'Hygienist', 'Behavior' 등이며, 매개중심성 상위 단어들은 'Dental', 'Health', 'Oral', 'Hygiene', 'Student' 등으로 나타났다. 시기별 연결중심성 핵심 키워드를 살펴본 결과, 1기에서는 Health (0.227), Dental (0.136), Hygiene (0.136) 등, 2기에서는 Health (0.242), Dental (0.177), Hygiene (0.113) 등, 3기에서는 Health (0.200), Dental (0.176), Oral (0.082) 등, 4기에서는 Dental (0.235), Health (0.206), Oral (0.147) 등의 단어들이 나타났다. 각 시기별로 매개중심성은 1기에서는 Oral (0.281)과 Health (0.199)의 매개중심성이 높게 나타났으며, 2기에서는 Dental (0.205)과 Health (0.169)가 높게 나와 매개역할의 비중이 높다가 Hygiene (0.112), Hygienist (0.054), Oral (0.053) 등으로 매개역할의 비중이 분산되는 것을 알 수 있었다. 3기에서는 Health (0.258)와 Dental (0.246)의 매개중심성이 높게 나타났으며, 4기에서는 Oral (0.364)과 Health (0.353), Dental (0.333)의 매개중심성이 높게 나타났다. 이상의 결과를 바탕으로 향후 치위생학 연구에 있어 학문 주제에 대한 다양성과 다각화를 모색하여 많은 연구가 이루어지길 기대한다.

의미네트워크 분석법을 이용한 근대 건축문화유산의 보존과 활용에 관한 사회적 논의 분석 - 부산광역시 근대건조물 구)한성은행 부산지점(청자빌딩)을 중심으로 - (An Analysis of Social Discussion on Preservation and Utilization of Modern Architectural Heritage using Semantic Network Analysis - Focussed on the former Busan Branch of Hansung Bank(Cheong-Ja Bldg) as a Modern Heritage -)

  • 안재철
    • 대한건축학회논문집:계획계
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    • 제35권7호
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    • pp.101-108
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    • 2019
  • In this research, I conducted a semantic network analysis centering on media articles on purchasing, revitalizing, and utilizing the former Busan branch of Hansung Bank, a modern architectural heritage. We sought the most efficient analysis elements for the analysis of the social arguments about preservation and utilization embedded in media articles. For this reason, Degree Centrality measures how many connections the word described in the media article has, and Betweenness Centrality measures the influence that controls the flow of information through correlation I examined. In addition, keyword that express the theme well examined the aggregation structure in each sub-network. In this research, in theoretical terms, it makes sense in that the social discussion embedded in the article of the mass media is grasped empirically through semantic network analysis of words. Methodological aspect is best when it includes nouns and adjectives and the distance between words is more than four words in the analysis of the cohesive structure of the semantic network to determine whether the influence of social discussions is best assessed through the connection between words to media articles.

네트워크 텍스트 분석법을 활용한 STEAM 교육의 연구 논문 분석 (Analysis of Articles Related STEAM Education using Network Text Analysis Method)

  • 김방희;김진수
    • 한국초등과학교육학회지:초등과학교육
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    • 제33권4호
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    • pp.674-682
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    • 2014
  • This study aims to analyze STEAM-related articles and to look into the trend of research to present implications for research directions in the future. To achieve the research purpose, the researcher searched by key words, 'STEAM' and 'Convergence Education' through the RISS. Subjects of analysis were titles of 181 articles in journal articles and conference papers published from 2011 through 2013. Through an analysis of the frequency of the texts that appeared in the titles of the papers, key words were selected, the co-occurrence matrix of the key words was established, and using network maps, degree centrality and betweenness centrality, and structural equivalence, a network text analysis was carried out. For the analysis, KrKwic, KrTitle, UCINET and NetMiner Program were used, and the results were as follows: in the result of the text frequency analysis, the key words appeared in order of 'program', 'development', 'base' and 'application'. Through the network among the texts, a network built up with core hubs such as 'program', 'development', 'elementary' and 'application' was found, and in the degree centrality analysis, 'program', 'elementary', 'development' and 'science' comprised key issues at a relatively high value, which constituted the pivot of the network. As a result of the structural equivalence analysis, regarding the types of their respective relations, it was analyzed that there was a similarity in four clusters such as the development of a program (1), analysis of effects (2) and the establishment of a theoretical base (1).

빅데이터를 활용한 골프웨어에 관한 인식 연구 (A Study of Perception of Golfwear Using Big Data Analysis)

  • 이아름;이진화
    • 한국의류산업학회지
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    • 제20권5호
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    • pp.533-547
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    • 2018
  • The objective of this study is to examine the perception of golfwear and related trends based on major keywords and associated words related to golfwear utilizing big data. For this study, the data was collected from blogs, Jisikin and Tips, news articles, and web $caf{\acute{e}}$ from two of the most commonly used search engines (Naver & Daum) containing the keywords, 'Golfwear' and 'Golf clothes'. For data collection, frequency and matrix data were extracted through Textom, from January 1, 2016 to December 31, 2017. From the matrix created by Textom, Degree centrality, Closeness centrality, Betweenness centrality, and Eigenvector centrality were calculated and analyzed by utilizing Netminer 4.0. As a result of analysis, it was found that the keyword 'brand' showed the highest rank in web visibility followed by 'woman', 'size', 'man', 'fashion', 'sports', 'price', 'store', 'discount', 'equipment' in the top 10 frequency rankings. For centrality calculations, only the top 30 keywords were included because the density was extremely high due to high frequency of the co-occurring keywords. The results of centrality calculations showed that the keywords on top of the rankings were similar to the frequency of the raw data. When the frequency was adjusted by subtracting 100 and 500 words, it showed different results as the low-ranking keywords such as J. Lindberg in the frequency analysis ranked high along with changes in the rankings of all centrality calculations. Such findings of this study will provide basis for marketing strategies and ways to increase awareness and web visibility for Golfwear brands.

네트워크 텍스트 분석을 이용한 한국가정과교육학회지 논문의 연구 동향 분석 (Research Trend Analysis of Publications in the Journal of Home Economics Education Association Using Network Text Analysis)

  • 이윤정;김은정;김지선
    • 한국가정과교육학회지
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    • 제31권4호
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    • pp.1-18
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    • 2019
  • 이 연구는 네트워크 텍스트 분석을 이용하여 가정과교육 분야의 연구동향을 분석하였다. 2003년 7월부터 2018년 12월 사이에 한국가정과교육학회지에 게재된 586편의 논문의 주제를 소셜 네트워크 분석프로그램인 Netminer 4의 텍스트분석 도구를 이용하여 주제어들의 출현빈도와 중심성 분석(연결중심성, 근접중심성, 매개중심성), 시기별 LDA 분석 등을 실시하였다. 그 결과는 다음과 같다. 첫째, 전반적으로 출현 빈도가 높은 단어들은 부모, 문화, 단원, 건강, 진로, 소비, 실천성 등이었다. 주제어 네트워크 분석 결과, 연결중심성은 부모, 관리가 가장 높았고, 근접중심성은 부모, 남학생, 매개중심성은 남학생, 단원 등이 가장 높게 나타났다. 둘째, 2003년부터 2018년까지의 연구를 4개 시기로 나누어 중심성 분석을 실시한 결과, 네 시기 모두 교육, 가정, 목적, 수업, 중학교, 학교 등 출현 빈도수가 높은 단어들은 유사하였으나, 시기별로는 제3, 제4시기에는 '목적'이라는 단어가, 제4시기에는 '과정' 이라는 단어가 두드러지게 나타났다. 셋째, 시기별 중심성 분석 결과 중심성의 종류와 무관하게 각 시기에 중요한 역할을 하는 단어들은 일정한 것으로 나타났다. 넷째, LDA 분석을 통한 토픽 변화를 분석하였을 때 교육과정, 교과서, 가족건강성, 교수학습, 평가, 식생활, 외모관리, 소비 등은 모든 시기에 지속적으로 등장하였다. 4개 시기의 토픽은 점차 다양화되고, 세분화되며, 심화되는 경향을 보였다. 연구를 통해 교육과정의 변화와 국가정책이 반영되어 새롭게 등장한 토픽인 교사연수와 안전이 주제어로 도출되었으며, 상대적으로 연구의 관심이 낮았던 토픽은 주거임이 드러나 학자들의 관심과 연구 활성화가 요구된다고 할 것이다. 이 연구는 2000년대 이후 한국가정과교육학계에서 이루어진 연구들의 주요 관심사를 파악할 수 있었다는 점과 관심사들의 순위를 제시하였다는 점에서 의미가 있다.

언어 네트워크 분석을 통한 화장행동 연구동향 분석 (Language network analysis of make-up behavior research)

  • 백경진
    • 복식문화연구
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    • 제27권3호
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    • pp.274-284
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    • 2019
  • Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers' interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

텍스트네트워크분석을 적용하여 탐색한 국내 시뮬레이션간호교육 연구주제 동향 (Simulation Nursing Education Research Topics Trends Using Text Network Analysis)

  • 박찬숙
    • 동서간호학연구지
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    • 제26권2호
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    • pp.118-129
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    • 2020
  • Purpose: The purpose of this study was to analyze the topic trend of domestic simulation nursing education research using text network analysis(TNA). Methods: This study was conducted in four steps. TNA was performed using the NetMiner (version 4.4.1) program. Firstly, 245 articles from 4 databases (RISS, KCI, KISS, DBpia) published from 2008 to 2018, were collected. Secondly, keyword-forms were unified and representative words were selected. Thirdly, co-occurrence matrices of keywords with a frequency of 2 or higher were generated. Finally, social network-related measures-indices of degree centrality and betweenness centrality-were obtained. The topic trend over time was visualized as a sociogram and presented. Results: 178 author keywords were extracted. Keywords with high degree centrality were "Nursing student", "Clinical competency", "Knowledge", "Critical thinking", "Communication", and "Problem-solving ability." Keywords with high betweenness centrality were "CPR", "Knowledge", "Attitude", "Self-efficacy", "Performance ability", and "Nurse." Over time, the topic trends on simulation nursing education have diversified. For example, topics such as "Neonatal nursing", "Obstetric nursing", "Pediatric nursing", "Blood transfusion", "Community visit nursing", and "Core basic nursing skill" appeared. The core-topics that emerged only recently (2017-2018) were "High-fidelity", "Heart arrest", "Clinical judgment", "Reflection", "Core basic nursing skill." Conclusion: Although simulation nursing education research has been increasing, it is necessary to continue studies on integrated simulation learning designs based on various nursing settings. Additionally, in simulation nursing education, research is required not only on learner-centered educational outcomes, but also factors that influence educational outcomes from the perspective of the instructors.

소셜 네트워크 분석을 활용한 항공서비스 품질 비교 (Comparisons of Airline Service Quality Using Social Network Analysis)

  • 박주현;이현철
    • 산업경영시스템학회지
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    • 제42권3호
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    • pp.116-130
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    • 2019
  • This study investigates passenger-authored online reviews of airline services using social network analysis to compare the differences in customer perceptions between full service carriers (FSCs) and low cost carriers (LCCs). While deriving words with high frequency and weight matrix based on the text analysis for FSCs and LCCs respectively, we analyze the semantic network (betweenness centrality, eigenvector centrality, degree centrality) to compare the degree of connection between words in online reviews of each airline types using the social network analysis. Then we compare the words with high frequency and the connection degree to gauge their influences in the network. Moreover, we group eight clusters for FSCs and LCCs using the convergence of iterated correlations (CONCOR) analysis. Using the resultant clusters, we match the clusters to dimensions of two types of service quality models ($Gr{\ddot{o}}nroos$, Brady & Cronin (B&C)) to compare the airline service quality and determine which model fits better. From the semantic network analysis, FSCs are mainly related to inflight service words and LCCs are primarily related to the ground service words. The CONCOR analysis reveals that FSCs are mainly related to the dimension of outcome quality in $Gr{\ddot{o}}nroos$ model, but evenly distributed to the dimensions in B&C model. On the other hand, LCCs are primarily related to the dimensions of process quality in both $Gr{\ddot{o}}nroos$ and B&C models. From the CONCOR analysis, we also observe that B&C model fits better than $Gr{\ddot{o}}nroos$ model for the airline service because the former model can capture passenger perceptions more specifically than the latter model can.