• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.164-169
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• 2022

토픽 모델링은 비즈니스 분석이나 기술 동향 파악 등 다방면에서 많이 사용되고 있는 기술이다. 하지만 대표적인 방법인 LDA와 같은 비지도학습의 경우, 그 알고리즘 구조상 문서의 수가 많을 때 토픽 모델링이 가능하다. 본 논문에서는 문서의 수가 적은 경우도, 키워드 및 키프레이즈를 이용한 군집화를 통해 토픽 모델링을 하고 감성분석을 통해 토픽에 대한 분석도 제시하였다. 이에 필요한 데이터 제작 및 키워드 추출, 키워드 기반 감성분석, 키워드 임베딩 및 군집화를 구현하였고, 결과를 정성적으로 보았을 때 유의미한 분석이 되는 것을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.223-226
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• 2006

가상현실 기술은 3 차원 가상공간 및 물체를 시각화하는데 중점을 두고 있다. 이는 사용자가 3 차원으로 데이터를 충분히 활용하지 못하고, 시각자료로만 사용하게 되는 요인이 된다. 이를 보완하기 위해 시각 정보뿐만 아니라 구조 및 관계에 대한 정보까지도 효과적으로 활용 할 수 있는 연구가 필요하다. 따라서 본 연구에서는 외형뿐만 아니라 내부적인 구조와 관계에도 의미를 부여하기 위하여 3 차원 건축물에 XML 기반의 토픽맵을 적용하였다. 전통 건축물의 공포 부분을 모델링하고, 각각의 객체가 사용자에 의해 조작이 가능하도록 하였으며, 객체들의 구조와 연결관계를 분석하고, 정의된 구조 및 관계를 토대로 토픽맵을 작성하였다. 작성된 토픽맵은 모델링 데이터에 적용 가능하도록 DOM 을 이용하여 변환하였다. 이 연구를 통해 아무리 복잡한 구조물이라도 그에 대한 구조 정보를 쉽게 파악할 수 있었고, 계층적 연결 관계도 쉽게 파악 할 수 있었다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.367-375
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• 2021

This study aimed to identify the knowledge structure of researches on 'untact' and derived implications for directions for the studies using text mining. The study included network analysis and topic modelling of keywords and abstracts from 171 thesis published until October 2020. Centrality analysis showed that 'untact' studies had been focused on service, usage, consumption, technology and online. From the topic modelling, 6 topics such as 'COVID-19 and socio-technological change', 'needs and utilization of education contents', 'technology and service for user convenience', 'product marketing and sales', 'service design of the company', 'influence factors of usage and consumption' were extracted. Keywords that connect each topic were technology, service, usage, consumption, needs and factor. Exploratory analysis of 'untact' researches using text mining provides useful results for development of 'untact' studies.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.329-331
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• 2021

본 연구에서는 코로나19 관련 연구논문의 연구주제를 탐색하고 동향을 검토하고 있다. 또한 감성분석을 통해 부정적인 어조가 강한 경고가 되는 주제들을 알아본다. 잠재 디리슐레 할당(LDA)를 이용하여 총 8개의 토픽을 발견하 였고, 이를 구조적 토픽 모델링(STM)과 비교하여 비교적 안정적인 결과임을 확인하였다. 또한 k-means 군집 알고리즘을 통해 각 토픽별로 세부 연구주제를 발견하였고 주성분 분석을 이용하여 이를 시각적으로 표현하였다. 감성분석을 통해 각 토픽별 긍정적, 부정적인 단어들을 살펴보고 감성점수를 계산하여 연구논문의 주된 어조를 파악하였는데, 특히 생물 의학 관련, 국제적 역학관계, 심리적 영향과 관련된 연구에서 부정적인 어조가 강한 것으로 나타나 해당 부문에 대해서 주의와 관심이 요구된다. 향후 연구자들이 연구의 방향성을 탐색하고 정책결정자들이 연구지원 사업을 결정하는데 기초자료로 활용될 수 있을 것이다.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.23-48
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• 2022

The purpose of this study is to investigate the flow of domestic information literacy education research using keyword network analysis and topic modeling and to explore the direction of information literacy education in the future. For this reason, 306 academic papers related to information literacy education published in academic journals of the library and information science field in Korea were chosen. And through the preprocessing process for abstracts of the paper, total keyword appearance frequency, keyword appearance frequency by period, and keyword simultaneous occurrence frequency were analyzed. Subsequently, keyword network analysis analyzed the degree centrality, between centrality, and eigenvector centrality of keywords. Using structural topic modeling analysis, 15 topics -curriculum, information literacy effect, contents of information literacy education, school library education, information media literacy, information literacy ability evaluation index, library anxiety, public library program, health information literacy ability, digital divide, library assisted instruction improvement, research trend, information literacy model, and teacher role-were derived. In addition, the trend of topics by year was analyzed to confirm the change in relative weight by topic. Based on these results, the direction of information literacy education and the suggestions for follow-up research were presented.

• Korean Journal of Forensic Psychology
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• v.13 no.1
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• pp.23-52
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• 2022

In this study, focused group interviews with 24 incumbent judges were conducted on how they conceptualize public opinion and what attitude they take toward it in relation to judicial trials. The contents of the interviews were analyzed through grounded theory and topic modeling (STM). According to the grounded theory results, judges distinguished concepts such as social rules, socially accepted ideas, legal emotion, and public mood from public opinion, and subdivided public opinion into temporary and emotional reactions to specific legal cases and consistent attitudes toward law and policies. In addition, it was found that judges' attitudes toward public opinion and social norms differed depending on the type of cases or legal issues. Topic modeling results significantly corresponded to the grounded theory results. In this model, the effects of the types of cases dedicated to participants on topical prevalence were statistically significant.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.302-305
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• 2019

국민 청원 사이트가 뛰어난 접근성과 신속성으로 인하여 국민들로부터 많은 관심을 받고 있다. 현재 국민청원 사이트의 카테고리 분류는 '미래', '성장동력' 등을 포함한 16개의 카테고리 및 기타로 구성되어 있으나 그 기준이 모호하여 많은 청원글들이 기타 카테고리로 분류되고 있는 상황이다. 이는 청원글의 내용을 명확히 반영하지 않고 미리 정의된 카테고리 구조를 사용하고 있는데서 기인한다고 할 수 있다. 본 논문에서는 보다 구체적으로 정의된 카테고리를 정의하고자 추천 순으로 1,500개의 청원글을 수집하였고, 수집된 청원글의 내용을 바탕으로 카테고리 구조를 추출하였다. 먼저, k-평균 알고리즘을 적용하여 청원글을 군집하여 대분류를 정의하였고, 보다 구체적인 세부 분류를 정의하기 위하여 토픽모델링을 실시하였다. 본 논문에서 제시하는 계층적 카테고리 구조는 청원글의 내용을 바탕으로 대분류와 세부분류로 구성된 것이므로 새로운 청원글을 등록하거나 분류하는 데 적절한 것으로 보인다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.763-778
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• 2022

In this study we aim to identify the core technologies that play central roles along with the peripheral technologies that contribute to the technology convergence in digital healthcare. A total of 376 korean-patents related to healthcare were gathered from 2011 to 2020, and a topic modeling technique and a network analysis were conducted on the collected data. Six major topics were derived through the topic modeling procedure which are "data collection", "signal measurement", "health management", "data transmission", "diagnostic treatment", and "measurement device". Each of the six topics were analyzed to depict relations among technologies, specify the convergence characteristics, and identify the core-technology through centrality analysis. The study illustrates the present status of digital healthcare technology development and the technological convergence in South Korea and is anticipated to help establish policies to foster healthcare industry.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.30-45
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• 2022

This study explored the issues of industrial mathematics in online news articles and online forums in Korea and the US by using text mining and compared the results. Text data about industrial mathematics were collected from news articles of Naver, a major portal site, and postings and replies on Clien as resources of Korea, and from news articles by the New York Times and CNN as well as postings and replies on Reddit as resources of the US. Structural topic modeling analyses were performed, the major results of which were as follows. First, news articles in Korea mainly dealt with the necessity of industrial mathematics and government support. On the contrary, the news articles in the US focused more on various fields where industrial mathematics fields were utilized. Second, in Korea, the same number of issues with different topics were discussed in news articles and online forums, whereas in the US more issues were covered in news articles than in online forums. It was suggested academic implications for researchers and practical implications for the government for settling industrial mathematics in Korea.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.81-92
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• 2022

In this study, interview scripts written in the dropout application was analyzed using BERTopic,, and parental influence, academic adaptation, university dissatisfaction was derived as major topics. An empirical study was conducted through a survey of 199 current students with researchmodel composed of those factors affecting dropout intention. The result shows that parental influence had a negative effect on academic adaptation and university satisfaction. Academic adaptation and university satisfaction had a negative effect on the dropout intention. parental influence did not directly affect the dropout intention, but had an indirect positive effect through academic adaptation and university/major satisfaction. The result shows that university satisfaction and academic adaptation is important factor to lower the dropout intention of students who chose current university by parental influence.