• 제목/요약/키워드: Topic Trends

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Topic Modeling Analysis of Social Media Marketing using BERTopic and LDA

  • YANG, Woo-Ryeong;YANG, Hoe-Chang
    • 산경연구논집
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    • 제13권9호
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    • pp.37-50
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    • 2022
  • Purpose: The purpose of this study is to explore and compare research trends in Korea and overseas academic papers on social media marketing, and to present new academic perspectives for the future direction in Korea. Research design, data and methodology: We used English abstract of research paper (Korea's: 1,349, overseas': 5,036) for word frequency analysis, topic modeling, and trend analysis for each topic. Results: The results of word frequency and co-occurrence frequency analysis showed that Korea researches focused on the experiential values of users, and overseas researches focused on platforms and content. Next, 13 topics and 12 topics for Korea and overseas researches were derived from topic modeling. And, trend analysis showed that Korean studies were different from overseas in applying marketing methods to specific industries and they were interested in the short-term performance of social media marketing. Conclusions: We found that the long-term strategies of social media marketing and academic interest in the overall industry will necessary in the future researches. Also, data mining techniques will necessary to generate more general results by quantifying various phenomena in reality. Finally, we expected that continuous and various academic approaches for volatile social media is effective to derive practical implications.

토픽모델링을 활용한 무역분야 연구동향 분석 (A Study on the Research Trends in Int'l Trade Using Topic modeling)

  • 이지훈;김정숙
    • 무역학회지
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    • 제45권3호
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    • pp.55-69
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    • 2020
  • This study examines the research trends and knowledge structure of international trade studies using topic modeling method, which is one of the main methodologies of text mining. We collected and analyzed English abstracts of 1,868 papers of three Korean major journals in the area of international trade from 2003 to 2019. We used the Latent Dirichlet Allocation(LDA), an unsupervised machine learning algorithm to extract the latent topics from the large quantity of research abstracts. 20 topics are identified without any prior human judgement. The topics reveal topographical maps of research in international trade and are representative and meaningful in the sense that most of them correspond to previously established sub-topics in trade studies. Then we conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics. We discovered 2 hot topics(internationalization capacity and performance of export companies, economic effect of trade) and 2 cold topics(exchange rate and current account, trade finance). Trade studies are characterized as a interdisciplinary study of three agendas(i.e. international economy, International Business, trade practice), and 20 topics identified can be grouped into these 3 agendas. From the estimated results of the study, we find that the Korean government's active pursuit of FTA and consequent necessity of capacity building in Korean export firms lie behind the popularity of topic selection by the Korean researchers in the area of int'l trade.

임신성 당뇨와 모유수유에 대한 연구 동향 분석: 텍스트네트워크 분석과 토픽모델링 중심 (A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling)

  • 이정림;김영지;곽은주;박승미
    • 한국간호교육학회지
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    • 제27권2호
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    • pp.175-185
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    • 2021
  • Purpose: The aim of this study was to identify core keywords and topic groups in the 'Gestational diabetes mellitus (GDM) and Breastfeeding' field of research for better understanding research trends in the past 20 years. Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups. Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', 'fetus', 'hypoglycemia', 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were 'cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: 'cardiovascular disease', 'obesity', 'complication prevention strategy', 'support of breastfeeding', 'educational program' and 'management of GDM'. Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.

LDA를 이용한 국제지적연구의 주제와 추세확인에 관한 연구: 특히 FIG Peer Review Journal을 중심으로 (A Study on Identifying Topics and Trends in International Cadastral Research Using LDA: With Special Reference to the FIG Peer Review Journal)

  • 김윤기
    • 지적과 국토정보
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    • 제48권1호
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    • pp.15-33
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    • 2018
  • 본 연구의 주된 목적은 LDA를 이용하여 국제지적연구의 주제와 연구추세를 확인하는 것이었다. 이러한 연구목적을 달성하기 위해 나는 LDA와 국제지적연구에 관한 선행연구를 검토하였고 이를 기반으로 4 개의 연구 질문을 설정하였다. 이러한 연구 질문에 답을 구하기 위해 나는 FIG Peer Review Journal에 2008년 1월1일 부터 2017년 10월 31일 사이에 발표된 370편의 논문들을 LDA를 이용하여 분석하였다. 분석의 결과 나는 국제지적연구에 12개의 주요 주제가 존재하고 있음을 확인하였다. 그리고 이러한 주제 중에 가장 영향력 있는 주제는 topic 2 (지적정보시스템)로 확인되었으며 또한 topic 5 (토지개발과 토지행정)도 전체 문서에서 중요한 역할을 수행하고 있는 주제로 파악되었다. 이두 주제는 지난 10년 동안 추세선이 매우 활발하게 움직인 가장 인기 있는 주제들로서 앞으로의 지적연구에서도 주도적인 역할을 수행할 것이 틀림없다.

텍스트마이닝을 이용한 정보보호 연구동향 분석 (Research Trends Analysis of Information Security using Text Mining)

  • 김태경;김창식
    • 디지털산업정보학회논문지
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    • 제14권2호
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    • pp.19-25
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    • 2018
  • With the development of IT technology, various services such as artificial intelligence and autonomous vehicles are being introduced, and many changes are taking place in our lives. However, if secure security is not provided, it will cause many risks, so the information security becomes more important. In this paper, we analyzed the research trends of main themes of information security over time. In order to conduct the research, 'Information Security' was searched in the Web of Science database. Using the abstracts of theses published from 1991 to 2016, we derived main research topics through topic modeling and time series regression analysis. The topic modeling results showed that the research topics were Information technology, system access, attack, threat, risk management, network type, security management, security awareness, certification level, information protection organization, security policy, access control, personal information, security investment, computing environment, investment cost, system structure, authentication method, user behavior, encryption. The time series regression results indicated that all the topics were hot topics.

Text Mining 기법을 활용한 항공안전관리 이슈 분석 (Analysis of Aviation Safety Management Issues using Text Mining)

  • 권문진;이장룡
    • 한국항공운항학회지
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    • 제31권4호
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    • pp.19-27
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    • 2023
  • In this study, a total of 2,584 domestic research papers with the keywords "Aviation Safety" and "Aviation Accidents" were subjected to Text Mining analysis. Various text mining techniques, including keyword frequency analysis, word correlation analysis, network analysis, and topic modeling, were applied to examine the research trends in the field of aviation safety. The results revealed a significant increase in research using the keyword "Aviation Safety" since 2015, with over 300 papers published annually. Through keyword frequency analysis, it was observed that "Aircraft" was the most frequently mentioned term, followed by "Drones" and "Unmanned Aircraft." Phi coefficients were calculated for words closely related to "Aircraft," "Aviation," "Drones," and "Safety." Furthermore, topic modeling was employed to identify 12 distinct topics in the field of aviation safety and aviation accidents, allowing for an in-depth exploration of research trends.

특허의 토픽 모델링을 활용한 증강현실 기술 모니터링 (Monitoring Augmented Reality Technology Using Topic Modeling of Patents)

  • 오승현;최하영;윤장혁
    • 대한산업공학회지
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    • 제43권3호
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    • pp.213-228
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    • 2017
  • Augmented reality (AR), which is a live direct or indirect view of a real-world environment combined with virtual objects, has grown rapidly owing to its wide application potential. Despite the growth of AR technology and its increased attraction, however, little attention has been paid to identifying sub-technologies of this technology and their evolving trends based on the data encompassing industrial competition. In the present study, therefore we collect AR-related patents granted until 2015 and then identify technology topics constituting AR technology by applying topic modeling to the patents' textual data. Subsequently, this study determines dynamic evolving trends with respect to those identified technology topics using indicators and maps based on the technology topics' patents and citations. The contributions of this study are twofold; it provides an overall understanding of AR technology's evolving trends based on text mining of AR patents and will assist technology experts in academia and industry in determining further R&D in the near future.

토픽모델링과 에고 네트워크 분석을 활용한 스마트 헬스케어 연구동향 분석 (Research Trend Analysis on Smart healthcare by using Topic Modeling and Ego Network Analysis)

  • 윤지은;서창진
    • 디지털콘텐츠학회 논문지
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    • 제19권5호
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    • pp.981-993
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    • 2018
  • 스마트 헬스케어는 ICT 분야와 의료서비스 분야가 융 복합 된 분야로 다양한 분야에서 학제 간 융 복합 연구가 활발히 이루어지고 있다. 본 연구는 토픽모델링(Topic Modeling)과 에고 네트워크 분석(Ego Network Analysis)을 활용하여 스마트 헬스케어 연구동향을 살피는데 그 목적이 있다. 이를 위해 2001년부터 2018년 4월까지 Scopus에 게재된 2,690편을 대상으로 텍스트 분석, 각 기간별 빈도분석, 토픽모델링, 워드 클라우드, 에고 네트워크 분석을 수행하였다. 토픽 모델링 분석 결과 8개의 주요 연구토픽이 도출되었다. 8개 주요 연구토픽은 "AI in healthcare", " Smart hospital", "Healthcare platform", " blockchain in healthcare", "Smart health data", "Mobile healthcare", "Wellness care", "Cognitive healthcare" 순으로 나타났다. 토픽모델링 결과를 보다 심도 있게 살펴보기 위해 연구토픽별 에고 네트워크 분석을 하였다. 이를 통해 스마트 헬스케어 연구동향을 파악하고, 향후 연구의 방향성을 수립하는데 시사점을 제시하고자 한다.

청소년 임신에 대한 연구 동향 분석: 텍스트 네트워크 분석과 토픽 모델링 (A study on research trends for pregnancy in adolescence: Focusing on text network analysis and topic modeling)

  • 박승미;곽은주;박혜옥;홍정은
    • 한국간호교육학회지
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    • 제30권2호
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    • pp.149-159
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    • 2024
  • Purpose: The aim of this study was to identify core keywords and topic groups in the "adolescent pregnancy" field of research for a better understanding of research trends in the past 10 years. Methods: Topics related to adolescent pregnancy were extracted from 3,819 articles that were published in journals between January 2013 and July 2023. Abstracts were retrieved from five databases (MEDLINE, CINAHL, Embase, RISS, and KISS). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Text network analysis and topic modeling were performed using NetMiner 4.3.3. Results: The most important keywords were "health," "woman," "risk," "group," "girl," "school," "service," "family," "program," and "contraception." Five topic groups were identified through topic modeling. Through the topic modeling analysis, five themes were derived: "health service," "community program for school girls," "risks for adult women," "relationship risks," and "sexual contraceptive knowledge." Conclusion: This study utilized text network analysis and topic modeling to analyze keywords from abstracts of research conducted over the past decade on adolescent pregnancy. Given that adolescent pregnancy leads to physical, mental, social, and economic issues, it is imperative to provide integrated intervention programs, including prenatal/postnatal care, psychological services, proper contraception methods, and sex education, through school and community partnerships, as well as related research studies. Nurses can play a vital role by actively engaging in prevention efforts and directly supporting and educating socially disadvantaged adolescent mothers, which could significantly contribute to improving their quality of life.

토픽모델링을 활용한 농촌연구 동향분석 (An Analysis on the Rural Research Trends using Topic Modeling)

  • 김가은;정유경;임영훈
    • 농촌계획
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    • 제29권4호
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    • pp.81-92
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    • 2023
  • The purpose of this study is to identify rural research topics, differences in research topics over time, and key mediators through the analysis of academic research trends using topic modeling. This study analyzed a total of 1,183 articles published in the Journal of Rural Planning and Rural Society over a 23-year period (2000-2022). We categorized rural research topics into 30, examined the proportion of research in each topic, and identified major changes in research topics over time. We also identified key words that mediate between research topics. The study found that, first, rural research trends can be categorized into five types (resources and utilization, area/space, people, ecosystem/environment, and tourism), with area/space being the most studied. Subtopics include rural amenities, rural disappearance/village miniaturization, and rural landscape management. Second, the research topics for each period were different. In the first period(2003-2007), the main research topics were rural amenities and Agricultural production- based climate vulnerability assessment. In the second period(2008-2012), the main research topics were Rural extinction and village depopulation, and rural landscape management, and in the third period(2013-2017), the main research topics were rural sixth industrialization and rural ecotourism. In the fourth period(2018-2022), rural development planning and rural life services(life SOC) were the main research topics. The significance of this study is that it extends the existing method of analyzing research trends and provides basic data to enhance comprehensive insights and understanding of rural research.