• 제목/요약/키워드: Keyword Frequency Analysis

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Exploration of Research Trends in The Journal of Distribution Science Using Keyword Analysis

  • YANG, Woo-Ryeong
    • 산경연구논집
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    • 제10권8호
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    • pp.17-24
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    • 2019
  • Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.

스마트교육 연구동향에 대한 분석 연구 (A Study on the Research Trends of Smart Learning)

  • 김향화;오동인;허균
    • 수산해양교육연구
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    • 제26권1호
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    • pp.156-165
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    • 2014
  • The purpose of this study was to find research trends of smart learning. For this, we identified the research's characteristics such as the subject or keyword of research, method, data collection, and statistical analysis method. The 2,865 articles published from 1995 to 2013 were gathered from five Korean academic journals related to smart learning. Among them, research keyword, areas, research method, data collection method, and statistical analysis method were analyzed on 596 papers. The findings of this study were as follows: (a) Smart learning papers such keyword likes u-learning, m-learning, and smart-learning were emerging after 2006. Smart learning papers with ICT related topics were highly increased after 2000, but they were decreased after 2006. Smart learning papers with e-learning related keywords were steadily increased after 2000 through 2013. (b) The research field of deign had the highest portion in smart learning research, but managing had the lowest portion. (c) Development was mainly used as a research method. Both questionnaire and experiment were mainly used for collecting data methods. T-test and frequency analysis were mainly used as statistical analysis methods.

키워드 네트워크 분석을 활용한 글로벌가치사슬(GVCs) 연구동향 분석 (A Study on Global Value Chains(GVCs) Research Trends Based on Keyword Network Analysis )

  • 박현용;최영준;이가은
    • 무역학회지
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    • 제45권5호
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    • pp.239-260
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    • 2020
  • This research was conducted on 176 GVCs-related research papers listed in the Index of Korean Academic Writers. The analysis methodology used the keyword network analysis methodology of big data analysis. For the comprehensive analysis of research trends, the research trends through word frequency (TF), important topic (TF-IDF), and topical modeling were analyzed in 176 papers. In addition, the research period of GVCs was divided into the early stages of the first study (2003-2014), the second phase of the study (2015-2017), and the third phase of the study (2018-2020). According to the comprehensive analysis, the GVCs research was conducted with the keyword 'value added' as the center, focusing on the keywords of export (trade), Korea, business, influence, and production. Major research topics were 'supporting corporate cooperation and capacity building' and 'comparative advantage with added value of overseas direct investment'. According to the analysis of major period-specific research trends, GVCs were studied in the early stages of the first phase of the study with global value chain trends and corporate production strategies. In the second research propulsion period, research was done in terms of trade value added. In the recent third phase of the study, small and medium-sized enterprises actively participated in the global value chain and actively researched ways to support the government. Through this study, the importance of the global value chain has been confirmed quantitatively and qualitatively, and it is recognized as an important factor to be considered in the strategy of enhancing industrial competitiveness and entering overseas markets. In particular, small and medium-sized companies' participation in the global value chain and support measures are being presented as important research topics in the future.

A study on Metaverse Consumer perception survey before and after Covid-19 using CONCOR analysis on BIG Data

  • Min, Byun Kwang;Hwan, Ryu Gi
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권4호
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    • pp.36-40
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    • 2022
  • Many parts of life have been changed due to the unprecedented coronavirus outbreak, and Noncontact has now become a general culture of society around the world. Also, many years later, after the Fourth Industrial Revolution, it is now deeply embedded in the human lifestyle. The purpose of this paper's research is to investigate the metaverse perception before and after Corona. It was confirmed that the number of metaverse, the central keyword, was 70971 before Corona, but 261767 after Corona, which was more than three times the frequency. In addition, it was confirmed that the number of COVID-19, the reference point of this study, increased significantly to 1,9236 during the pre-COVID-19 period. Through this, it can be inferred that the metaverse accelerated and developed significantly after the corona. Metaverse about Keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above. As such, it was confirmed that keywords for metaverse were changing before and after Corona, and as such, Consumers' perceptions were also changing.

키워드 네트워크 분석을 활용한 세계 크루즈산업 연구동향 (Research Trends in Global Cruise Industry Using Keyword Network Analysis)

  • 장세은;이수호
    • 한국항해항만학회지
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    • 제38권6호
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    • pp.607-614
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    • 2014
  • 세계적으로 해양산업은 크루즈산업에 많은 관심과 연구가 대폭적으로 이루어지고 있고 우리나라도 미래의 잠재력 있는 국가동력산업의 하나로 인식하고는 있으나 크루즈산업의 연구동향 분석 연구는 국내외에 활발히 이루어지고 있지 않다. 따라서 우선 세계 크루즈산업을 연구하고 이해하기 위해서는 최근에 다양한 산업에 대한 연구동향을 분석한 방법을 활용하여 크루즈산업에도 적용할 필요가 있다. 본 논문의 목적은 외국 유명저널에 발표된 크루즈산업과 관련된 학술논문에서 제시하고 있는 키워드와 논문을 매개로 한 키워드 네트워크를 구축하여 복잡계의 네트워크 분석에서 사용하는 연결 중심성과 매개 중심성 분석방법으로 시대별로 나누어 시각화하여 살펴봄으로써 세계 크루즈산업의 연구동향을 심층적으로 관찰하여 논의하는 것이다. 본 연구에서 제시된 키워드 빈도는 Zipf의 법칙을 따르고 노드의 연결정도는 멱함수 분포를 보여주고 있어 언어네트워크에서 분석하는 키워드 네트워크와 동일함을 관찰한다. 연구방법론으로는 키워드 네트워크 분석을 위하여 사회연결망 프로그램인 넷마이너 4.0을 사용하여 여러 가지 중심성 측정방법 중 키워드 상위 20개의 빈도순위를 비교하여 빈도순위와 가장 가까운 중심성 측정방법을 선택하여 크루즈산업의 연구동향을 분석한다. 특히 크루즈산업의 연구동향이 연도 기간별로 어떠한 변화를 가져왔는지를 살펴보기 위해 2000년 이전과 2000년 이후로 크게 대별하여 나누고 2000년 이후에는 5년 주기로 각 기간별 공통적으로 나타나는 연결 중심성이 높은 최상위의 키워드인 cruise와 tourism 노드를 중심으로 매개 중심성이 높은 것들의 키워드 네트워크를 시각화하여 논의한다. 연구결과에서 흥미롭게도 2010-2014의 기간에 새로운 노드로 China가 등장하여 최상위의 키워드들을 연결하고 있는 것은 최근 급성장하고 있는 중국의 크루즈산업의 발전 양상을 보여준다. 그러므로 본 연구에서 사용하는 키워드 네트워크 분석은 각 연도 기간별 네트워크의 다른 종류의 숫자와 크고 작은 중심축 군집 네트워크의 숫자의 증감뿐 아니라 중심축 군집 네트워크의 중심에 있는 키워드 간의 연결 분석을 용이하게 해주어 기간별 연구동향을 파악하는데 유용한 방법임을 확인할 수 있었다.

RFID 연구 논문에 대한 주제어 분석 (A Keyword analysis on the RFID research papers)

  • 양병학
    • 대한안전경영과학회지
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    • 제14권3호
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    • pp.221-227
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    • 2012
  • This research is a key words analysis on Radio Frequency Identification. Key words were collected from Korean research papers in the electronic library DBpia. 700 papers published from 2001 to 2011 were included. The number of collected key words is 1460. The trend of publishing research papers was increased rapidly from 2005, reached peak at 2009 and decreased after 2010. Majority of key words were related to hardware, information technology and standardization. Selected 128 key words were analyzed and clustered by social network analysis to find a relationship among key words on RFID.

Nowcast of TV Market using Google Trend Data

  • Youn, Seongwook;Cho, Hyun-chong
    • Journal of Electrical Engineering and Technology
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    • 제11권1호
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    • pp.227-233
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    • 2016
  • Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.

컴퓨터공학 분야 학술 논문 데이터베이스를 이용한 키워드 연관 네트워크 기반 지식지도 (A Knowledge Map Based on a Keyword-Relation Network by Using a Research Paper Database in the Computer Engineering Field)

  • 정보석;권영근;곽승진
    • 정보처리학회논문지D
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    • 제18D권6호
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    • pp.501-508
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    • 2011
  • 최근 여러 분야에서 활용되고 있는 지식지도는 대량의 정보 속에 숨겨진 특징을 찾아서 그 의미를 파악할 수 있도록 가시적인 형태의 결과를 보여주는 것을 말한다. 본 논문에서는 2000년부터 2010년까지 컴퓨터 공학 분야의 국내 학술지에 게재된 논문들의 데이터베이스를 활용하여 연구동향 분석을 위한 키워드 연관 네트워크 기반의 지식지도를 제안하였다. 그 지식지도를 통해 키워드 연관 네트워크에서 개별 키워드가 속한 연결 요소의 크기 변화를 살펴봄으로써 관련 연구 주제의 영향력 변화를 추론할 수 있었다. 또한, 랜덤 네트워크와의 비교를 통해 키워드 연관 네트워크에서 최대 연결 요소의 크기가 상대적으로 매우 작으며, 상호 관련성이 높은 키워드 쌍들의 그룹이 밀집되어 있음을 보였다. 이는 최대 연결 요소에 대응하는 연구 분야가 크지 않으며 여러 소규모의 연구 주제들이 느슨한 형태로 연결되어 있음을 암시한다. 이러한 분석 결과들은 단순히 개별 키워드의 사용 빈도수 등을 분석하는 전통적인 방식으로는 얻기 어렵다는 점에서 본 논문에서 제안한 지식지도가 연구동향 분석의 방법이 될 수 있다.

텍스트마이닝 기법을 이용한 모바일 피트니스 애플리케이션 주요 요인 분석 : 사용자 경험 관점 (An Analysis on Key Factors of Mobile Fitness Application by Using Text Mining Techniques : User Experience Perspective)

  • 이소현;김진솔;윤상혁;김희웅
    • 한국IT서비스학회지
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    • 제19권3호
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    • pp.117-137
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    • 2020
  • The development of information technology leads to changes in various industries. In particular, the health care industry is more influenced so that it is focused on. With the widening of the health care market, the market of smart device based personal health care also draws attention. Since a variety of fitness applications for smartphone based exercise were introduced, more interest has been in the health care industry. But although an amount of use of mobile fitness applications increase, it fails to lead to a sustained use. It is necessary to find and understand what matters for mobile fitness application users. Therefore, this study analyze the reviews of mobile fitness application users, to draw key factors, and thereby to propose detailed strategies for promoting mobile fitness applications. We utilize text mining techniques - LDA topic modeling, term frequency analysis, and keyword extraction - to draw and analyze the issues related to mobile fitness applications. In particular, the key factors drawn by text mining techniques are explained through the concept of user experience. This study is academically meaningful in the point that the key factors of mobile fitness applications are drawn by the user experience based text mining techniques, and practically this study proposes detailed strategies for promoting mobile fitness applications in the health care area.

텍스트 마이닝 분석을 통한 수학교육 연구 동향 분석 (A Text Mining Analysis for Research Trend about the Mathematics Education)

  • 진미르;고호경
    • East Asian mathematical journal
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    • 제35권4호
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    • pp.489-508
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    • 2019
  • In this paper we used text mining method to analyze journals of mathematics education posterior to the year of 2016. To figure out trends of mathematics education research. we analyzed the key words largely mentioned in the recent mathematics education journals by Term Frequency and Term Frequency-Inverse Document Frequency method. We also looked at how these keywords match up with the key words that appear of education to prepare for future society. This result can infer the characteristics of mathematics education research in the aspect upcoming research topics.