• Title/Summary/Keyword: Keyword Trends

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Fintech Trends and Mobile Payment Service Anlaysis in Korea: Application of Text Mining Techniques (국내 핀테크 동향 및 모바일 결제 서비스 분석: 텍스트 마이닝 기법 활용)

  • An, JungKook;Lee, So-Hyun;An, Eun-Hee;Kim, Hee-Woong
    • Informatization Policy
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    • v.23 no.3
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    • pp.26-42
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    • 2016
  • Recently, with the rapid growth of the O2O market, Fintech combining the finance and ICT technology is drawing attention as innovation to lead "O2O of finance", along with Fintech-based payment, authentication, security technology and related services. For new technology industries such as Fintech, technical sources, related systems and regulations are important but previous studies on Fintech lack in-depth research about systems and technological trends of the domestic Fintech industry. Therefore, this study aims to analyze domestic Fintech trends and find the insights for the direction of technology and systems of the future domestic Fintech industry by comparing Kakao Pay and Samsung Pay, the two domestic representative mobile payment services. By conducting a complete enumeration survey about the tweets mentioning Fintech until June 2016, this study visualized topics extraction, sensitivity analysis and keyword analyses. According to the analysis results, it was found that various topics have been created in the technologies and systems between 2014 and 2016 and different keywords and reactions were extracted between topics of Samsung Pay based on "devices" such as Galaxy and Kakao Pay based on "service" such as KakaoTalk. This study contributes to analyzing the unstructured data of social media by period by using social media mining and quantifying the expectations and reactions of consumers to services through the sentiment analysis. It is expected to be the foundation of Fintech industry development by presenting a strategic direction to Fintech related practitioners.

Analysis of interest in implant using a big data: A web-based study (빅 데이터를 이용한 임플란트에 대한 관심도 분석: 웹 기반 연구)

  • Kong, Hyun-Jun
    • The Journal of Korean Academy of Prosthodontics
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    • v.59 no.2
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    • pp.164-172
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    • 2021
  • Purpose: The purpose of this study was to analyze the level of interest that common Internet users have in dental implant using a Google Trends, and to compare the level of interest with big data from National Health Insurance Service. Materials and methods: Google Trends provides a relative search volume for search keywords, which is the average data that visualizes the frequency of searches for those keywords over a specific period of time. Implant was selected as the search keyword to evaluate changes in time flows of general Internet users' interest from 2015 to 2019 with trend line and 6 month moving average. Relative search volume for implant was analyzed with the number of patients who received National Health Insurance coverage for implant. Interest in implant and conventional denture was compared and popular related search keywords were analyzed. Results: Relative search volume for implant has increased gradually and showed a significant positive correlation with the total number of patients (P<.01). Interest in implant was higher than denture for most of the time. Keywords related to implant cost were most frequently observed in all years and related search on implant procedure was increasing. Conclusion: Within the limitations of this study, the public interest in dental implant was gradually increasing and specific areas of interest were changing. Web-based Google Trends data was also compared with traditional data and significant correlation was confirmed.

A Convergence Study of the Research Trends on Stress Urinary Incontinence using Word Embedding (워드임베딩을 활용한 복압성 요실금 관련 연구 동향에 관한 융합 연구)

  • Kim, Jun-Hee;Ahn, Sun-Hee;Gwak, Gyeong-Tae;Weon, Young-Soo;Yoo, Hwa-Ik
    • Journal of the Korea Convergence Society
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    • v.12 no.8
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    • pp.1-11
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    • 2021
  • The purpose of this study was to analyze the trends and characteristics of 'stress urinary incontinence' research through word frequency analysis, and their relationships were modeled using word embedding. Abstract data of 9,868 papers containing abstracts in PubMed's MEDLINE were extracted using a Python program. Then, through frequency analysis, 10 keywords were selected according to the high frequency. The similarity of words related to keywords was analyzed by Word2Vec machine learning algorithm. The locations and distances of words were visualized using the t-SNE technique, and the groups were classified and analyzed. The number of studies related to stress urinary incontinence has increased rapidly since the 1980s. The keywords used most frequently in the abstract of the paper were 'woman', 'urethra', and 'surgery'. Through Word2Vec modeling, words such as 'female', 'urge', and 'symptom' were among the words that showed the highest relevance to the keywords in the study on stress urinary incontinence. In addition, through the t-SNE technique, keywords and related words could be classified into three groups focusing on symptoms, anatomical characteristics, and surgical interventions of stress urinary incontinence. This study is the first to examine trends in stress urinary incontinence-related studies using the keyword frequency analysis and word embedding of the abstract. The results of this study can be used as a basis for future researchers to select the subject and direction of the research field related to stress urinary incontinence.

Study on Research Trends (2001~2020) of the Baekdudaegan Mountains with Big Data Analyses of Academic Journals (학술논문 빅데이터 분석을 활용한 백두대간에 관한 연구동향(2001~2020) 분석)

  • Lee, Jinkyu;Sim, Hyung Seok;Lee, Chang-Bae
    • Journal of Korean Society of Forest Science
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    • v.111 no.1
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    • pp.36-49
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    • 2022
  • The purpose of this study was to analyze domestic research trends related to the Baekdudaegan Mountains in the last two decades. In total, 551 academic papers and keyword data related to the Baekdudaegan Mountains were collected using the "Research and Information Service Section" and analyzed using "big data" analysis programs, such as Textom and UCINET. Papers related to the Baekdudaegan Mountains were published in 177 academic journals, and 229 papers (41.6% of all published papers) were published between 2011 and 2015. According to word frequency data (N-gram analyses), the major research topic over the past 20 years was "species diversity." According to CONCOR analysis results, the main research could be divided into 15 areas, the most important of which was "species diversity," followed by "vegetation restoration and management," and "culture." Ecological research comprised 12 groups with a frequency of 78.8%; humanities and social research comprised 2 groups with a frequency of 15.6%. Overall, our study of research areas and quantitative data analyses provides valuable information that could help establish policy formulation.

A Study on the Development of Interior Design Service for Autonomous Vehicles - Focusing on STEEP analysis Techniques - (자율주행차 인테리어 디자인서비스 개발연구 - STEEP 분석 기법을 적용한 사례 중심으로 -)

  • Kang, Taeho;Cho, Jounghyung
    • Journal of Service Research and Studies
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    • v.11 no.3
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    • pp.43-54
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    • 2021
  • This study focused on indoor spaces and convenience devices among vehicle interior designs suitable for the autonomous driving era, and presented an interior design model for future automobiles by applying the STEEP analysis method. The service design methodology is applied to deal with changes in display devices installed for the purpose of rearranging layouts and providing driver-centered information. Changes in types and installation locations of displays for various purposes such as connected and infotainment are expected. In particular, through this analysis, trends and experiences through indoor interior research in future self-driving cars will be studied, and subsequent studies will be used as basic data for actual development and application. Key drivers were extracted after deriving future trends linking the research project conducted in five stages to STEEP and consulting experts through FGI. Through this, it was later presented as a direction for indoor design. Through user-centered participatory design methods, emotional keyword derivation methods were used, summarized the derived drivers in five major trends in the future society, and each derived drivers were grouped to consider the relevant technology fields, and added elements to the autonomous driving level. This is an indoor ray viewed from the perspective of various social issues as well as personal tendencies in the future self-driving car industry.

A Study on Analysis of Research Trends and Intellectual Structure in the Overseas Cataloging Research (해외 목록학 연구동향 및 지적구조 분석)

  • Ji Won Lee;Sung Sook Lee
    • Journal of the Korean Society for information Management
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    • v.41 no.1
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    • pp.367-387
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    • 2024
  • This study aims to identify the recent trends and intellectual structure of international research in the field of catalog, which is undergoing a major change due to the enactment of new standards and rules and the anticipated future. For this purpose, we collected 680 articles published in the 14 years since 2010 and analyzed 1,942 author keywords extracted from them after preprocessing. The main findings of the analysis are as follows First, overseas cataloging research has seen notable growth since 2017. Second, the most frequent research topics were: cataloging, metadata, RDA, university libraries, authority control, linked data, FRBR, catalog, LCSH, libraries, andonline cataloging. Third, the research themes were divided into two clusters, one related to the traditional aspects of library cataloging and the other related to the more recently discussed topics of authority control, cooperative cataloging, RDA, and linked data, which were further subdivided into 14 subclusters. Fourth, we looked at the growth index and standard performance index of the 14 keyword clusters and found that all but one cluster showed growth in terms of discipline growth. This study is significant in that it can be used as a basis for predicting the future development of inventories for Korean academia and the field and for related education.

Research trends in Journal of The Korean Society for School & Community Health Education on Vulnerable Populations from 2000 to 2023: Based on the elderly and people with disabilities (한국학교·지역보건교육학회지 2000년~2023년 취약 계층 연구 동향: 노인과 장애인을 중심으로)

  • Ye-Soon Kim;Young-Hee Nam
    • The Journal of Korean Society for School & Community Health Education
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    • v.25 no.2
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    • pp.71-81
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    • 2024
  • Purpose: This study aims to identify research trends in papers related to the elderly and the disabled published in the journal of Korean society for school & community health education from 2000 to 2023 and seek the direction of the academic development of this journal in the future. Method: A total of 26 articles related to the elderly and the disabled, who are vulnerable groups, were analyzed by year by analyzing the specific subjects, research themes, research design, data collection methods, and keywords of papers published from 2000 to 2023. Results: Looking at the research subjects, studies on the elderly (18 studies) accounted for a larger proportion than studies on the disabled (8 studies). Research themes in the field of healthy living practices for the elderly (44.4%) and research in the field of mental health management (37.5%) for the disabled accounted for a high proportion. The design of research were mostly quantitative and cross-sectional studies. Data collection is mostly based on secondary data. In studies targeting the elderly, keywords appeared in the following order: 'Health' and 'Elderly'. And research targeting the disabled appeared in the following order: 'Disabilities', 'Health', and 'COVID-19'. Additionally, research on the elderly and the disabled has recently shown an increasing trend. Conclusion: Research on the elderly and the disabled has been conducted in line with the purpose of the Korean society for school & community health education, However, In terms of quantitative expansion and qualitative research, research themes, research designs, and data collection methods must be diversified. Methods, public perception. Additionally, research on vulnerable groups that fit the public health promotion and health education paradigm is needed.

Analyzing Research Trends in Blockchain Studies in South Korea Using Dynamic Topic Modeling and Network Analysis (다이나믹 토픽모델링 및 네트워크 분석 기법을 통한 블록체인 관련 국내 연구 동향 분석)

  • Kim, Donghun;Oh, Chanhee;Zhu, Yongjun
    • Journal of the Korean Society for information Management
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    • v.38 no.3
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    • pp.23-39
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    • 2021
  • This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.

A Study on Environmental research Trends by Information and Communications Technologies using Text-mining Technology (텍스트 마이닝 기법을 이용한 환경 분야의 ICT 활용 연구 동향 분석)

  • Park, Boyoung;Oh, Kwan-Young;Lee, Jung-Ho;Yoon, Jung-Ho;Lee, Seung Kuk;Lee, Moung-Jin
    • Korean Journal of Remote Sensing
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    • v.33 no.2
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    • pp.189-199
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    • 2017
  • Thisstudy quantitatively analyzed the research trendsin the use ofICT ofthe environmental field using the text mining technique. To that end, the study collected 359 papers published in the past two decades(1996-2015)from the National Digital Science Library (NDSL) using 38 environment-related keywords and 16 ICT-related keywords. It processed the natural languages of the environment and ICT fields in the papers and reorganized the classification system into the unit of corpus. It conducted the text mining analysis techniques of frequency analysis, keyword analysis and the association rule analysis of keywords, based on the above-mentioned keywords of the classification system. As a result, the frequency of the keywords of 'general environment' and 'climate' accounted for 77 % of the total proportion and the keywords of 'public convergence service' and 'industrial convergence service' in the ICT field took up approximately 30 % of the total proportion. According to the time series analysis, the researches using ICT in the environmental field rapidly increased over the past 5 years (2011-2015) and the number of such researches more than doubled compared to the past (1996-2010). Based on the environmental field with generated association rules among the keywords, it was identified that the keyword 'general environment' was using 16 ICT-based technologies and 'climate' was using 14 ICT-based technologies.

Home training trend analysis using newspaper big data and keyword analysis (신문 빅데이터와 키워드 분석을 이용한 홈트레이닝 트렌드 분석)

  • Chi, Dong-Cheol;Kim, Sang-Ho
    • Journal of the Korea Convergence Society
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    • v.12 no.6
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    • pp.233-239
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    • 2021
  • Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.