• 제목/요약/키워드: LDA토픽모델링

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Perceived Healthiness of Healthy Restaurants Based on Network Analysis and LDA Topic Modeling (네트워크 분석과 LDA 토픽 모델링을 활용한 건강한 레스토랑의 지각된 건강성 요인)

  • Minji Kim;Sunhee Seo
    • Knowledge Management Research
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    • v.25 no.3
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    • pp.201-230
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    • 2024
  • This study aimed to identify the factors contributing to perceived healthiness by analyzing consumer reviews of healthy restaurants. While previous studies have primarily focused on the healthiness of food products, comprehensive research from the perspective of restaurants through online review analysis is limited. To achieve this, co-occurrence network analysis and LDA topic modeling, methods of text mining, were used to investigate consumers' health-related perceptions and preferences for healthy restaurants based on a large dataset of online reviews. The analysis revealed that consumers emphasize various health-related factors such as taste, ingredient categories, freshness, price, nutritional content, healthy options, and menu diversity when choosing healthy restaurants. These factors significantly influence the evaluation and selection of restaurants. Notably, it was found that the taste of food offered in healthy restaurants is closely linked to the perception of healthiness, highlighting the importance of a healthy taste derived from ingredients. In conclusion, this study provides practical insights into how healthy restaurants can reflect and meet consumers' health perceptions and suggests strategic directions for the food and dining industry to respond to health trends.

Analysis of Domestic and Foreign Financial Security Research Activities and Trends through Topic Modeling Analysis (토픽모델링 분석 기법을 활용한 국내외 금융보안 분야 연구동향 분석)

  • Chae, Ho-Geun;Lee, Gi-Hyun;Lee, Joo-Yeoun
    • Journal of Korea Society of Industrial Information Systems
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    • v.26 no.1
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    • pp.83-95
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    • 2021
  • In this study, major research trends at home and abroad were compared and analyzed in order to derive key research fields in the financial security field and to suggest directions. To this end, 689 domestic and 20,736 foreign data were collected from domestic and international academic journal DB, and major research fields related to financial security were extracted through LDA analysis. After that, hot & cold topics were derived through time series linear regression analysis. As a result of the analysis, studies related to government policy issues, personal information, and accredited certification were derived as promising research fields in Korea. In the case of foreign countries, related studies were drawn to develop advanced security systems such as cryptographic protocols and quantum security. Recently, it has become possible to apply various security technologies in Korea through the abolition of public certification. Accordingly, as changes in promising research fields are expected, the results of this study are expected to contribute to the establishment and development of a successful roadmap for domestic financial security.

Investigating the Trends of Research for the Small Business Owners (소상공인 연구 동향 분석)

  • Bang, Mi-Hyun;Lee, Young-Min
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.73-80
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    • 2022
  • In this study, prior studies of 280 small business owners in Korea over the past two decades were comprehensively analyzed through keyword network and LDA topic modeling analysis, and overall views and trends in academia were examined. As core keywords, "sales" and "protection," which conflict with each other but are essential for stable and sustainable growth were selected, and 7 topics (Topic 1: start-up, topic 2: digital, topic 3: tax system, topic 4: capability, topic 5: coexistence, topic 6: regulation, and topic 7: funding) were drawn up. Based on the results of the analysis, the need to improve digital maturity for the continued growth and development of small business owners was raised, and the response at the pan-ministerial level and the stability of the performance of functions that can survive even after the new administration to solve the economic damage problems facing small business owners were suggested. In addition, attention to the long-term, speed, detail, and direction of government support in a new way, and a flexible approach to the negative way in which pre-allowance and post-regulation is given were suggested.

Keyword trends analysis related to the aviation industry during the Covid-19 period using text mining (텍스트마이닝을 활용한 Covid-19 기간 동안의 항공산업 관련 키워드 트렌드 분석)

  • Choi, Donghyun;Song, Bomi;Park, Dahyeon;Lee, Sungwoo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.2
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    • pp.115-128
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    • 2022
  • The purpose of this study is to conduct keyword trend analysis using articles data on the impact of Covid-19 in the aviation in dustry. In this study, related articles were extracted centering on the keyword "Airline" by dividing the period of 6months before and after Covid-19 occurrence. After that, Topic modeling(LDA) was performed. Through this, The main topic was extracted in the event of an epidemic such as Covid-19, It is expected to be used as primary data to predict the aviation industry's impact when occurrence like Covid-19.

A Study on the School Library Research Trends Using Topic Modeling (토픽모델링을 활용한 학교도서관 연구동향 분석)

  • Jung, Young-Joo;Kim, Hea-Jin
    • Journal of Korean Library and Information Science Society
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    • v.51 no.3
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    • pp.103-121
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    • 2020
  • This study aimed to analyze the research trends of school libraries from 1990 to July 2020. To this end, LDA topic modeling analysis was conducted to the domestic article abstracts related to school libraries. The total number of documents is 498 papers published by the four major domestic journals in Library and Information Science. The log-likelihood estimate criterion was used to determine the number of topics for topic modeling. As a result of the study, 27 topics were discovered, then, theory were categorized by eight subject areas: general, institutional system, building/equipment, operation/management, data organization, service, education, and others. The most popular research was library utilization classes (T27) and Information Utilization (T2). More than 20 studies were found in each evaluation index development (T13), school librarian placement (T24), learning information media utilization (T3), community public library (T7), library cooperation (T9), library use (T17), library research (T11), reading education (T4), collection development (T5), and education effects/teaching methods (T18).

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.

A Study on the Research Trends in the Fourth Industrial Revolution in Korea Using Topic Modeling (토픽모델링을 활용한 4차 산업혁명 분야의 국내 연구 동향 분석)

  • Gi Young Kim;Dong-Jo Noh
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.34 no.4
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    • pp.207-234
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    • 2023
  • Since the advent of the Fourth Industrial Revolution, related studies have been conducted in various fields including industrial fields. In this study, to analyze domestic research trends on the Fourth Industrial Revolution, a keyword analysis and topic modeling analysis based on the LDA algorithm were conducted on 2,115 papers included in the KCI from January 2016 to August 2023. As a result of this study, first, the journals in which more than 30 academic papers related to the Fourth Industrial Revolution were published were digital convergence research, humanities society 21, e-business research, and learner-centered subject education research. Second, as a result of the topic modeling analysis, seven topics were selected: "human and artificial intelligence," "data and personal information management," "curriculum change and innovation," "corporate change and innovation," "education change and jobs," "culture and arts and content," and "information and corporate policies and responses." Third, common research topics related to the Fourth Industrial Revolution are "change in the curriculum," "human and artificial intelligence," and "culture arts and content," and common keywords include "company," "information," "protection," "smart," and "system." Fourth, in the first half of the research period (2016-2019), topics in the field of education appeared at the top, but in the second half (2020-2023), topics related to corporate, smart, digital, and service innovation appeared at the top. Fifth, research topics tended to become more specific or subdivided in the second half of the study. This trend is interpreted as a result of socioeconomic changes that occur as core technologies in the fourth industrial revolution are applied and utilized in various industrial fields after the corona pandemic. The results of this study are expected to provide useful information for identifying research trends in the field of the Fourth Industrial Revolution, establishing strategies, and subsequent research.

Spatial analysis based on topic modeling using foreign tourist review data: Case of Daegu (외국인 관광객 리뷰데이터를 활용한 토픽모델링 기반의 공간분석: 대구광역시를 사례로)

  • Jung, Ji-Woo;Kim, Seo-Yun;Kim, Hyeon-Yu;Yoon, Ju-Hyeok;Jang, Won-Jun;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.8
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    • pp.33-42
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    • 2021
  • As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

Analysis of Topic Changes in Metaverse Application Reviews Before and After the COVID-19 Pandemic Using Causal Impact Analysis Techniques (Causal Impact 분석 기법을 접목한 COVID-19 팬데믹 전·후 메타버스 애플리케이션 리뷰의 토픽 변화 분석)

  • Lee, Sowon;Mijin Noh;MuMoungCho Han;YangSok Kim
    • Smart Media Journal
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    • v.13 no.1
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    • pp.36-44
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    • 2024
  • Metaverse is attracting attention as the development of virtual environment technology and the emergence of untact culture due to the COVID-19 pandemic. In this study, by analyzing users' reviews on the "Zepeto" application, which has recently attracted attention as a metaverse service, we tried to confirm changes in the requirements for the metaverse after the COVID-19 pandemic. To this end, 109,662 reviews of "Zepeto" applications written on the Google Play Store from September 2018 to March 2023 were collected, topics were extracted using LDA topic modeling technique, and topics were analyzed using the Causal Impact technique to examine how topics changed before and after based on "March 11, 2020" when the COVID-19 pandemic was declared. As a result of the analysis, five topics were extracted: application functional problems (topic1), security problems (topic 2), complaints about cryptocurrency (Zem) in the application (topic 3), application performance (topic 4), and personal information-related problems (topic 5). Among them, it was confirmed that security problems (topic 2) were most affected by the COVID-19 pandemic.