• 한국도서관정보학회지
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• 제48권4호
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• pp.235-258
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• 2017

본 연구에서는 최근 각광을 받고 있는 텍스트마이닝 기법인 LDA 토픽모델링과 이를 변형한 HDP 토픽모델링을 적용하여 국내 기록관리학의 연구동향을 분석하고자 한다. 이를 위해 국내 기록관리학 관련 학술지 2종과 문헌정보학 관련 학술지 4종에서 1997년부터 2016년까지 발표된 기록관리학 관련 논문 1,027건을 수집하고 적절한 전처리과정을 거친 후 LDA 토픽모델링과 HDP 토픽모델링을 각각 수행하였다. 또한 토픽모델링 시각화 도구인 LDAvis를 활용하여 토픽별 거리를 가시적으로 표현하고 세부 대표 키워드를 분석하였다. 두 토픽모델링을 비교한 결과, LDA 토픽모델링은 전반적으로 해당 도메인을 대표하는 주요 키워드로 빈도수에 영향을 많이 받았으며, HDP 토픽모델링은 각 토픽별 특징을 파악할 수 있는 특수한 키워드가 많이 도출되었다. 이를 통해 LDA는 국내 기록관리학 내에 거시적으로 대표되는 주제들을, HDP는 세부 주제별 미시적인 핵심 키워드를 도출하는데 효과적임을 알 수 있었다.

• 한국프랜차이즈경영연구
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• 제12권4호
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• pp.13-23
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• 2021

Purpose: This study aimed to derive clues for the franchise industry to overcome difficulties such as various legal regulations and social responsibility demands and to continuously develop by analyzing the research trends related to franchises published in Korea. Research design, data and methodology: As a result of searching for 'franchise' in ScienceON, abstracts were collected from papers published in domestic academic journals from 1994 to June 2021. Keywords were extracted from the abstracts of 1,110 valid papers, and after preprocessing, keyword analysis, TF-IDF analysis, and topic modeling using LDA algorithm, along with trend analysis of the top 20 words in TF-IDF by year group was carried out using the R-package. Results: As a result of keyword analysis, it was found that businesses and brands were the subjects of research related to franchises, and interest in service and satisfaction was considerable, and food and coffee were prominently studied as industries. As a result of TF-IDF calculation, it was found that brand, satisfaction, franchisor, and coffee were ranked at the top. As a result of LDA-based topic modeling, a total of 12 topics including "growth strategy" were derived and visualized with LDAvis. On the other hand, the areas of Topic 1 (growth strategy) and Topic 9 (organizational culture), Topic 4 (consumption experience) and Topic 6 (contribution and loyalty), Topic 7 (brand image) and Topic 10 (commercial area) overlap significantly. Finally, the trend analysis results for the top 20 keywords with high TF-IDF showed that 10 keywords such as quality, brand, food, and trust would be more utilized overall. Conclusions: Through the results of this study, the direction of interest in the franchise industry was confirmed, and it was found that it was necessary to find a clue for continuous growth through research in more diverse fields. And it was also considered an important finding to suggest a technique that can supplement the problems of topic trend analysis. Therefore, the results of this study show that researchers will gain significant insights from the perspectives related to the selection of research topics, and practitioners from the perspectives related to future franchise changes.

• 한국프랜차이즈경영연구
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• 제13권4호
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• pp.1-12
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• 2022

Purpose: In 2020, the franchise industry accomplished a significant growth compared to the previous year, as the number of franchise companies increased by 9.0% while the number of franchise brands increased by 12.5%. Despite growth in size, the Korean franchise industry underwent many negative incidents, such as franchise ownership sales to private equity funds, that led to deterioration of businesses. From this point of view, this study aims to make various proposals to help policy makers develop franchise industry policies by analyzing trends of the current and previous presidential administrations' franchise policies and regulations using newspaper articles. Research design, data and methodology: A total of 7,439 articles registered in Naver API from February 25, 2013 to November 29, 2021 were extracted. Among them, 34 unrelated video articles were deleted, and a total of 7,405 articles from both administrations were used for analysis. The R package was used for word frequency analysis, word clouding, word correlation analysis, and LDA (Latent Dirichlet Allocation) topic modeling. Results: The keyword frequency analysis shows that the most frequently mentioned keywords during the previous administration include 'no-brand', 'major company', 'bill', 'business field', and 'SMEs', and those mentioned during the current administration include 'industry' and 'policy'. As a result of LDA topic modeling, 9 topics such as 'global startups' and 'job creation' from the previous administration, and 10 topics such as 'franchise business' and 'distribution industry' from the current administration were derived. The results of LDAvis showed that the previous administration operated a policy based on mutual growth of large and small businesses rather than hostile regulations in the franchise business, whereas the current administration extended the regulation related to franchise business to the employment sector. Conclusions: The analysis of past two administrations' franchise policy, it can be suggested that franchisors and franchisees may complement each other in developing the Fair Transactions in Franchise Business Act and achieving balanced growth. Moreover, political support is needed for sound development of franchisors. Limitations and future research suggestions are presented at the end of this study.

• 산업경영시스템학회지
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• 제46권3호
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• 한국컴퓨터정보학회논문지
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• 제29권7호
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• pp.99-107
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• 2024

컴퓨터 관련 기술이 급변하는 환경에서 사이버 위협들은 새로운 기술과 함께 고도화되고 다양화되어 지속해서 등장하고 있다. 이에 본 연구에서는 보안 관련 뉴스 기사를 수집해서 LDA 토픽 모델링을 진행해 동향을 살펴보고자 한다. 이를 위해 2020년 1월부터 2023년 8월까지의 뉴스 기사를 수집하였으며 LDA 분석을 통해 주요 토픽을 도출하였다. 이후 토픽별 흐름을 파악하고 주요 기점에 대해 분석하였다. 분석 결과를 통해 2021년의 랜섬웨어 공격과 2023년의 가상자산거래소 해킹이 최근 보안 분야에서 큰 이슈인 것을 파악할 수 있다. 이를 통해 보안 이슈에 대한 동향을 확인하고, 앞으로 어떤 연구에 집중해야 하는지 확인해 볼 수 있다. 또한 최신 위협을 인지하고, 적절한 대응 전략을 지원할 수 있으며 효과적인 보안 대책의 개발에 기여할 것으로 기대된다.