• Title/Summary/Keyword: Topic Trend

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The Trend of Research in Journal of the Korean Society of Physical Medicine (대한물리의학회지(2006-2012)의 연구동향)

  • Roh, Jung-Suk
    • Journal of the Korean Society of Physical Medicine
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    • v.8 no.3
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    • pp.457-466
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    • 2013
  • PURPOSE: The purpose of this study was to investigate the trend of research in Journal of the Korean Society of Physical Medicine (JKSPM). METHODS: A total of 897 articles of JKSPM from Vol.1, No.1, 2006 to Vol.7, No.4, 2012 were reviewed in regard to research type, research level, subjects, research topic, statistic method, and researcher. RESULTS: The most common research type was experimental study(65%). The most common research level was level 2(randomized controlled trials; RCT)(55%). The most common age group of subject was age 11-30 group(55%). The most common diagnosis of subjects was stroke(49%). The main research topic of articles was therapeutic exercise(13.2%). Independent t-test was the most used statistic method. A professor was the most common researcher. The Daegu and Busan were the most common provinces that researcher works. CONCLUSION: This study showed the trend of research in JKSPM and helped readers to understand the trends of research in fields of physical therapy of Korea. In further studies, it is necessary to review systematically and intensively other journals in field of physical therapy.

Research Trend on Diabetes Mobile Applications: Text Network Analysis and Topic Modeling (당뇨병 모바일 앱 관련 연구동향: 텍스트 네트워크 분석 및 토픽 모델링)

  • Park, Seungmi;Kwak, Eunju;Kim, Youngji
    • Journal of Korean Biological Nursing Science
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    • v.23 no.3
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    • pp.170-179
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    • 2021
  • Purpose: The aim of this study was to identify core keywords and topic groups in the 'Diabetes mellitus and mobile applications' field of research for better understanding research trends in the past 20 years. Methods: This study was a text-mining and topic modeling study including four steps such as 'collecting abstracts', 'extracting and cleaning semantic morphemes', 'building a co-occurrence matrix', and 'analyzing network features and clustering topic groups'. Results: A total of 789 papers published between 2002 and 2021 were found in databases (Springer). Among them, 435 words were extracted from 118 articles selected according to the conditions: 'analyzed by text network analysis and topic modeling'. The core keywords were 'self-management', 'intervention', 'health', 'support', 'technique' and 'system'. Through the topic modeling analysis, four themes were derived: 'intervention', 'blood glucose level control', 'self-management' and 'mobile health'. The main topic of this study was 'self-management'. Conclusion: While more recent work has investigated mobile applications, the highest feature was related to self-management in the diabetes care and prevention. Nursing interventions utilizing mobile application are expected to not only effective and powerful glycemic control and self-management tools, but can be also used for patient-driven lifestyle modification.

A Study on the Research Topics and Trends in South Korea: Focusing on Particulate Matter (토픽모델링을 이용한 국내 미세먼지 연구 분류 및 연구동향 분석)

  • Park, Hyemin;Kim, Taeyong;Kwon, Daewoong;Heo, Junyong;Lee, Juyeon;Yang, Minjune
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.873-885
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    • 2022
  • The particulate matter (PM) has emerged as a hot topic around the world as it has been reported that PM is related to an increase in mortality and prevalence rates. In South Korea, the importance of PM has been recognized since the late 1990s, and various studies on PM have been conducted. This study investigated the PM research topics and trends for papers (D=2,764) published in Research Information Sharing Service (RISS) using topic modeling based on Latent Dirichlet Allocation (LDA). As a result, a total of 10 topics were identified in the whole papers, and the PM research topics were classified as 'PM reduction (Topic 1)', 'Government policy and management (Topic 2)', 'Characteristics of PM (Topic 3)', 'PM model (Topic 4)', 'Environmental education (Topic 5)', 'Bio (Topic 6)', 'Traffic (Topic 7)', 'Asian dust (Topic 8)', 'Indoor PM (Topic 9)', 'Human risk (Topic 10)'. In particular, the proportion of papers on topics 'Government policy and management (Topic 2)', 'PM model (Topic 4)', 'Environmental education (Topic 5)', and 'Bio (Topic 6)' to the toal number of papers increased over time (linear slope > 0). The results of this study provide the new literature review methodology related to particulate matter and the history and insight.

Topic modeling and topic change trend analysis for advanced construction technologies (건설신기술에 대한 토픽 모델링 및 토픽 변화추이 분석)

  • Jeong, Seong Yun;Kim, Nam Gon
    • Smart Media Journal
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    • v.10 no.4
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    • pp.102-110
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    • 2021
  • Currently, the advanced construction technology endorsement system is being operated to promote the development of domestic construction technology. We tried to examine the implicit meanings inherent in advanced construction technologies by analyzing the relationship between emerging vocabularies with high importance in relation to the advanced construction technologies endorsed through this system. For this purpose, 918 cases of advanced construction technology information were collected. Based on the endorsed year and summary of the advanced construction technologies, the importance of the emerging vocabularies was measured for each advanced construction technology. And, based on the LDA model, the degree of influence between related vocabularies was evaluated for each of the four topic areas. Topics according to the technical application fields were analyzed. From 1990 to 2021, the trend of changes in highly influential vocabularies by each topic was inferred. In the future, changes in the degree of influence of the topics of environment, machinery, facilities, and maintenance and reinforcement of structures and related technology fields were predicted.

Identifying research trends in the emergency medical technician field using topic modeling (토픽모델링을 활용한 응급구조사 관련 연구동향)

  • Lee, Jung Eun;Kim, Moo-Hyun
    • The Korean Journal of Emergency Medical Services
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    • v.26 no.2
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    • pp.19-35
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    • 2022
  • Purpose: This study aimed to identify research topics in the emergency medical technician (EMT) field and examine research trends. Methods: In this study, 261 research papers published between January 2000 and May 2022 were collected, and EMT research topics and trends were analyzed using topic modeling techniques. This study used a text mining technique and was conducted using data collection flow, keyword preprocessing, and analysis. Keyword preprocessing and data analysis were done with the RStudio Version 4.0.0 program. Results: Keywords were derived through topic modeling analysis, and eight topics were ultimately identified: patient treatment, various roles, the performance of duties, cardiopulmonary resuscitation, triage systems, job stress, disaster management, and education programs. Conclusion: Based on the research results, it is believed that a study on the development and application of education programs that can successfully increase the emergency care capabilities of EMTs is needed.

An Analysis of the Research Trends for Urban Study using Topic Modeling (토픽모델링을 이용한 도시 분야 연구동향 분석)

  • Jang, Sun-Young;Jung, Seunghyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.661-670
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    • 2021
  • Research trends can be usefully used to determine the importance of research topics by period, identify insufficient research fields, and discover new fields. In this study, research trends of urban spaces, where various problems are occurring due to population concentration and urbanization, were analyzed by topic modeling. The analysis target was the abstracts of papers listed in the Korea Citation Index (KCI) published between 2002 and 2019. Topic modeling is an algorithm-based text mining technique that can discover a certain pattern in the entire content, and it is easy to cluster. In this study, the frequency of keywords, trends by year, topic derivation, cluster by topic, and trend by topic type were analyzed. Research in urban regeneration is increasing continuously, and it was analyzed as a field where detailed topics could be expanded in the future. Furthermore, urban regeneration is now becoming a regular research field. On the other hand, topics related to development/growth and energy/environment have entered a stagnation period. This study is meaningful because the correlation and trends between keywords were analyzed using topic modeling targeting all domestic urban studies.

A Research on Difference Between Consumer Perception of Slow Fashion and Consumption Behavior of Fast Fashion: Application of Topic Modelling with Big Data

  • YANG, Oh-Suk;WOO, Young-Mok;YANG, Yae-Rim
    • The Journal of Economics, Marketing and Management
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    • v.9 no.1
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    • pp.1-14
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    • 2021
  • Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

Identification of Convergence Trend in the Field of Business Model Based on Patents (특허 데이터 기반 비즈니스 모델 분야 융합 트렌드 파악)

  • Sunho Lee;Chie Hoon Song
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.3
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    • pp.635-644
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    • 2024
  • Although the business model(BM) patents act as a creative bridge between technology and the marketplace, limited scholarly attention has been paid to the content analysis of BM patents. This study aims to contextualize converging BM patents by employing topic modeling technique and clustering highly marketable topics, which are expressed through a topic-market impact matrix. We relied on BM patent data filed between 2010 and 2022 to derive empirical insights into the commercial potential of emerging business models. Subsequently, nine topics were identified, including but not limited to "Data Analytics and Predictive Modeling" and "Mobile-Based Digital Services and Advertising." The 2x2 matrix allows to position topics based on the variables of topic growth rate and market impact, which is useful for prioritizing areas that require attention or are promising. This study differentiates itself by going beyond simple topic classification based on topic modeling, reorganizing the findings into a matrix format. T he results of this study are expected to serve as a valuable reference for companies seeking to innovate their business models and enhance their competitive positioning.

Research Trend Analysis by using Text-Mining Techniques on the Convergence Studies of AI and Healthcare Technologies (텍스트 마이닝 기법을 활용한 인공지능과 헬스케어 융·복합 분야 연구동향 분석)

  • Yoon, Jee-Eun;Suh, Chang-Jin
    • Journal of Information Technology Services
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    • v.18 no.2
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    • pp.123-141
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    • 2019
  • The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

Analysis of outdoor-wear research trends using topic modeling (토픽 모델링을 이용한 아웃도어웨어 연구 동향 분석)

  • Kihyang Han;Minsun Lee
    • The Research Journal of the Costume Culture
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    • v.31 no.1
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    • pp.53-69
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    • 2023
  • This study aims to analyze research trends regarding outdoor wear. For this purpose, the data-collection period was limited to January 2002-October 2022, and the collection consisted of titles of papers, academic names, abstracts, and publication years from the Research Information Sharing Service (RISS). Frequency analysis was conducted on 227 papers in total to check academic journals and annual trends, and LDA topic-modeling analysis was conducted using 20,964 tokens. Data pre-processing was performed prior to topic-modeling analysis; after that, topic-modeling analysis, core topic derivation, and visualization were performed using a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: experiential marketing and lifestyle, property and evaluation of outdoor wear, design and patterns of outdoor wear, outdoor-wear purchase behavior, color, designs and materials of outdoor wear, promotional strategies for outdoor wear, purchase intention and satisfaction depending on the brand image of outdoor wear, differences in outdoor wear preferences by consumer group. The results of topic-modeling analysis revealed that the topic, which includes a study on the design and material of outdoor wear and the pattern of jackets related to the overall shape, was the highest at 30.9% of the total topics. The next highest topic was also the design and color of outdoor wear, indicating that design-related research was the main research topic in outdoor wear research. It is hoped that analyzing outdoor wear research will help comprehend the research conducted thus far and reveal future directions.