• 한국조리학회지
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• 제23권4호
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• pp.22-32
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• 2017

The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

• Child Health Nursing Research
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• 제27권3호
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• pp.201-210
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• 2021

Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI). Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling. Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life". Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.

• 한국컴퓨터정보학회논문지
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• 제24권3호
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• pp.143-150
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• 2019

This study aimed to analyze the keyword related to Health Disparity in Korea through the method of keyword network analysis and to establish a basic database for suggesting ideas for prospective studies in physical education. To achieve the goal, this study crawled co-occured keyword with 'health' and 'disparity' from news casted in 20 different channels. The duration of the news was 3 months, from September 11th, 2018 to December 11th. The results are as follows. First, among the news during recent 3 months, there were 1,383 keyword related to health disparity and this study selected 173 keyword which had co-occured over 3 times. Second, the inclusiveness of the network was 97.674% and the density was .038. Third, analyzing news related to health disparity, 'mortality' was the most co-occured keyword and 'disparity', 'reinforcement', 'the most', 'health', '6 times', 'Seoul', 'half', 'medicine', and 'local' were shown similarly. And common keyword in 4 centrality were 13 keyword. Lastly, by analyzing eigenvector centrality, significantly different result has shown. 'Disparity' was the most co-occured keyword. Based on this result, this study showed the necessity for reinforcing the public physical education in public education system in Korea. In order to achieve it, the field of physical education must look beyond present elite-focused physical education to public physical activity.

• Child Health Nursing Research
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• 제29권3호
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• pp.182-194
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• 2023

Purpose: This study analyzed research trends in infant and toddler rearing behavior among family caregivers over a 10-year period (2010-2021). Methods: Text network analysis and topic modeling were employed on data collected from relevant papers, following the extraction and refinement of semantic morphemes. A semantic-centered network was constructed by extracting words from 2,613 English-language abstracts. Data analysis was performed using NetMiner 4.5.0. Results: Frequency analysis, degree centrality, and eigenvector centrality all revealed the terms ''scale," ''program," and ''education" among the top 10 keywords associated with infant and toddler rearing behaviors among family caregivers. The keywords extracted from the analysis were divided into two clusters through cohesion analysis. Additionally, they were classified into two topic groups using topic modeling: "program and evaluation" (64.37%) and "caregivers' role and competency in child development" (35.63%). Conclusion: The roles and competencies of family caregivers are essential for the development of infants and toddlers. Intervention programs and evaluations are necessary to improve rearing behaviors. Future research should determine the role of nurses in supporting family caregivers. Additionally, it should facilitate the development of nursing strategies and intervention programs to promote positive rearing practices.

• 한국콘텐츠학회논문지
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• 제20권9호
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• pp.29-42
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• 2020

본 연구의 목적은 소셜미디어 중 하나인 YouTube 동영상 사용자들이 남긴 의견을 추출하여 분석하는 질적연구방법을 제시한다. 이를 위해서 YouTube 동영상 사용자의견을 사용하여 사용과 충족 이론의 쾌락적 충족, 사회적 충족, 그리고 실용적 충족을 빈도분석과 토픽모델링을 통해 측정하였다. 측정결과, YouTube KBS 한국방송 채널 중 트로트 가수 조명섭 동영상을 사용자들이 시청하는 이유는 첫 번째로 높은 빈도를 보이는 것이 쾌락적 충족을 위해서였다. 다음 순으로 사회적 충족과 실용적 충족으로 나타났다. 단어-문서 네트워크 분석에서 연결정도중심성은 '응원', '감사', '화이팅', '최고' 등이 높게 나타났고, 매개중심은'감사', '응원', '화이팅'등의 단어가 높게 나타나 연결정도 중심성과 유사함을 보였다. 아이겐벡터중심성은 '사랑', '마음', '감사' 등의 단어가 높게 나타나 사용자들의 의견들에 가장 영향력이 높은 단어들임을 알 수 있다. 이는 YouTube의 트로트 가수 조명섭 동영상 시청자들 중 대다수가 동영상에 대해 사랑과 감사의 마음을 보이고 있음을 알 수 있다. 위의 세 가지 중심성 분석결과는 동영상을 시청하는 동기로 사용충족 이론의 쾌락적 충족과 사회적 충족 관련 단어들이 높은 값을 보이고 있다. 본 연구는 설문조사 기반의 구조방정식 모형을 따르지 않고, 질적분석연구를 자동화한 텍스트마이닝 기법을 사용하여 YouTube동영상을 사용하는 동기를 사용 및 충족 이론에 의해 밝혀냈다는 것에서 연구 함의를 찾을 수 있다.

• 대한지구과학교육학회지
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• 제14권2호
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• pp.173-192
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• 2021

본 연구는 야외지질답사에 관하여 2000년부터 2020년까지 선행된 연구를 분석함으로써 그 동안 이루어진 연구가 중점을 둔 과제를 살펴보고 이를 통해 앞으로 야외지질답사 연구의 방향과 시사점을 제시하고자 하는 목적을 지닌다. 자료 수집은 야외지질답사와 관련하여 ScienceON과 RISS에서 검색되는 학위논문, KCI 등재 학술지를 대상으로 이루어졌으며, 연구 제목에 대하여 언어 네트워크 방법을 이용하여 분석하였다. 분석은 전처리를 마친 자료를 언어 네트워크 방법으로 네트워크를 나타내어 시각화하고 빈도수와 중심성 분석을 실시하였다. 중심성 분석은 연결 중심성과 위세 중심성을 바탕으로 하였으며, 모든 분석은 전체 연구 기간과 2000년-20005년, 2006년-2010년, 2011년-2015년, 2016년-2020년으로 4개의 기간을 나누어 이루어졌다. 그 결과, 야외지질답사에 관한 연구는 야외지질학습장 개발에 보다 중점을 두고 있었으며, 특히 제주도가 학습장으로서 활발한 논의가 이루어졌다. 또한, 교사 보다는 학생을 대상으로 연구가 이루어졌으며, 이중 고등학생이 높은 빈도와 중심성을 나타내었다. 이외에도 야외지질답사의 교육적 효과에 관한 연구와 융합인재교육, 자유학기제 등과 같은 프로그램과 연계하거나 웹, 플래시 파노라마, 3D와 같이 간접적인 지질 답사 방안도 논의가 이루어졌음을 알 수 있다. 본 연구는 그 동안 이루어진 야외지질답사에 관한 연구를 되돌아봄으로써 향후 연구의 방향성을 시사하였다는 점에서 의의가 있다.

• 정보관리학회지
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• 제37권2호
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• pp.71-93
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• 2020

오늘날 다양한 질병의 출현과 빠르게 변화하는 의료환경에 보다 효과적으로 대처하기 위해 대학병원 내에서 여러 진료과들이 협업진료를 수행하고 있다. 이러한 협업진료는 매우 중요하며 의료 현장에서 이미 보편화되어 있다. 그럼에도 불구하고, 이에 대한 연구, 특히 진료과들이 어떻게 협업을 하고 있는지에 대한 연구는 전무하다. 따라서 본 연구는 대학병원 내의 진료과 간의 협업진료 관계를 탐색하여 진료협업 네트워크 특성들이 연도별 및 계절별로 어떻게 달라지는지를 고찰하는 것에 목적이 있다. 본 연구는 국내 A대학교 대학병원에서 이루어진 29개 진료과 사이의 협업 진료를 연도별 및 계절별로 나누어 29개 진료과 협업 네트워크를 분석하였다. 협업진료의 요청 및 피요청에 따라 방향네트워크를 구성하였으며, 매개중심성, 아이겐벡터중심성, 근접중심성 분석, 에고 네트워크 분석 및 팩션분석과 더불어 추후 인터뷰도 실시하였다. 본 연구는 최초의 진료과 간의 협업 네트워크 분석을 수행하였으며, 의료기관 내에서의 동선을 고려한 진료과의 위치 및 공간 구성에 새로운 통찰력을 제시할 것으로 기대된다.

• 품질경영학회지
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• 제44권2호
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• 대한간호학회지
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• 제49권5호
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• pp.538-549
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• 2019

Purpose: This study aimed to explore and compare the knowledge structure of pain management nursing research, between Korea and other countries, applying a text network analysis. Methods: 321 Korean and 6,685 international study abstracts of pain management, published from 2004 to 2017, were collected. Keywords and meaningful morphemes from the abstracts were analyzed and refined, and their co-occurrence matrix was generated. Two networks of 140 and 424 keywords, respectively, of domestic and international studies were analyzed using NetMiner 4.3 software for degree centrality, closeness centrality, betweenness centrality, and eigenvector community analysis. Results: In both Korean and international studies, the most important, core-keywords were "pain," "patient," "pain management," "registered nurses," "care," "cancer," "need," "analgesia," "assessment," and "surgery." While some keywords like "education," "knowledge," and "patient-controlled analgesia" found to be important in Korean studies; "treatment," "hospice palliative care," and "children" were critical keywords in international studies. Three common sub-topic groups found in Korean and international studies were "pain and accompanying symptoms," "target groups of pain management," and "RNs' performance of pain management." It is only in recent years (2016~17), that keywords such as "performance," "attitude," "depression," and "sleep" have become more important in Korean studies than, while keywords such as "assessment," "intervention," "analgesia," and "chronic pain" have become important in international studies. Conclusion: It is suggested that Korean pain-management researchers should expand their concerns to children and adolescents, the elderly, patients with chronic pain, patients in diverse healthcare settings, and patients' use of opioid analgesia. Moreover, researchers need to approach pain-management with a quality of life perspective rather than a mere focus on individual symptoms.

• 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.