• 제목/요약/키워드: research topic analysis

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텍스트 분석을 활용한 국내 자연환경복원 연구동향 분석 (Text Analysis on the Research Trends of Nature Restoration in Korea)

  • 이길상;정예림;송영근;이상혁;손승우
    • 한국환경복원기술학회지
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    • 제27권2호
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    • pp.29-42
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    • 2024
  • As a global response to climate and biodiversity challenges, there is an emphasis on the conservation and restoration of ecosystems that can simultaneously reduce carbon emissions and enhance biodiversity. This study comprised a text analysis and keyword extraction of 1,100 research papers addressing nature restoration in Korea, aiming to provide a quantative and systematic evaluation of domestic research trends in this field. To discern the major research topics of these papers, topic modeling was applied and correlations were established through network analysis. Research on nature restoration exhibited a mainly upward trend in 2002-2022 but with a slight recent decline. The most common keywords were "species," "forest," and "water". Research topics were broadly classified into (1) predictions of habitat size and species distribution, (2) the conservation and utilization of natural resources in urban areas, (3) ecosystems and landscape managements in protected areas, (4) the planting and growth of vegetation, and (5) habitat formation methods. The number of studies on nature restoration are increasing across various domains in Korea, with each domain experiencing professional development.

사용자 리뷰 토픽분석을 활용한 모바일 쇼핑 앱 고객만족도에 관한 연구 (A Study on Customer Satisfaction of Mobile Shopping Apps Using Topic Analysis of User Reviews)

  • 김광국;김용환;김자희
    • 한국전자거래학회지
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    • 제23권4호
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    • pp.41-62
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    • 2018
  • 현재 모바일 쇼핑 시장의 빠른 성장에도 불구하고 주요 사업자들은 심한 경쟁 속에서 지속적인 영업적자를 기록하고 있다. 이 문제를 해결하기 위해서는 모바일 쇼핑 시장은 과도한 경쟁보다는 고객만족도와 고객충성도를 높이기 위한 연구들이 요구된다. 그러나 기존의 연구들은 기술수용 모형과 문헌연구를 기반으로 요인을 추출하고 있어 고객의 직접적인 요구를 반영하는 데 한계가 있다. 본 연구는 모바일 쇼핑 앱 사용자들의 직접적인 요구사항을 도출하기 위하여 사용자 리뷰 토픽분석을 시행하여 고객만족도에 영향을 미치는 구체적이고 다양한 요인들을 도출하였다. 그리고 미국 고객만족도 지표 모형을 참조한 구조방정식 연구모형을 수립하여 도출된 요인들이 고객만족도에 미치는 중요도를 평가하고 고객만족도가 고객 불평과 고객충성도에 주는 영향을 실증 분석하였다. 본 연구에서 제안한 토픽분석과 구조방정식을 연계한 연구 프레임워크는 다른 모바일 서비스의 고객만족도 연구에도 적용될 수 있을 것으로 기대된다.

토픽모델링을 활용한 물리학 독서감상문 텍스트의 교육과정 연계성 분석 (Curriculum Relevance Analysis of Physics Book Report Text Using Topic Modeling)

  • 임정훈
    • 한국도서관정보학회지
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    • 제53권2호
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    • pp.333-353
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    • 2022
  • 본 연구는 '물리학' 수업에서 교과독서 활동으로 작성된 독후감상문의 교육과정 연계성을 분석하는데 목적이 있다. 연구를 수행하기 위해 교과독서 활동으로 작성한 332편의 물리학 독서감상문을 수집하여 키워드와 키워드들의 연결 관계를 분석하고, STM(Structural Topic Modeling)을 적용하여 토픽을 추출하였다. 분석 결과, 물리학 독서감상문의 주요 키워드는 '생각', '내용', '설명', '이론', '사람', '이해' 등으로 나타났으며, 도출된 키워드의 영향력과 연결 관계를 살펴보기 위해 연결중심성, 매개중심성, 위세중심성을 제시하였다. 토픽모델링 분석 결과, 물리학 교육과정과 관련된 11개 토픽이 추출되었으며, 3과목(물리학I, 물리학II, 과학사), 6개 영역(힘과 운동, 현대물리, 파동, 열과 에너지, 서양과학사, 과학이란 무엇인가)에서 교육과정 연계성을 확인할 수 있었다. 본 연구의 결과는 추후 교과 특성을 반영한 교과독서를 보다 체계적으로 시행할 수 있는 근거자료로 활용할 수 있을 것이다.

텍스트 마이닝을 이용한 시대별 청소년 문제 토픽 분석 (Topic Analysis on the Adolescent Problem Using Text Mining)

  • 조경원;조주연
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 추계학술대회
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    • pp.203-204
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    • 2018
  • This research was conducted to identify adolescent problems in internet articles. This research defines adolescent problems as diverse issues related to adolescents and examine how it was dealt in the media to find out how different categories and the aspect of adolescent problems are changing by time. The result of the research was that in 1990's, education policy and family were mainly dealt with when it came to adolescent problems. As the era is changing, adolescent problems were far diversified compared to the past, and each problems are dealt with similar importance. This research is significant in that it does not only examine the social trend adolescent problems but also expand the range of adolescent counselling and utilizes quantitative analysis in considering diversity to provide new information.

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온라인 리뷰의 텍스트 마이닝에 기반한 한국방문 외국인 관광객의 문화적 특성 연구 (A study on cultural characteristics of foreign tourists visiting Korea based on text mining of online review)

  • 야오즈옌;김은미;홍태호
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권4호
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    • pp.171-191
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    • 2020
  • Purpose The study aims to compare the online review writing behavior of users in China and the United States through text mining on online reviews' text content. In particular, existing studies have verified that there are differences in online reviews between different cultures. Therefore, the purpose of this study is to compare the differences between reviews written by Chinese and American tourists by analyzing text contents of online reviews based on cultural theory. Design/methodology/approach This study collected and analyzed online review data for hotels, targeting Chinese and US tourists who visited Korea. Then, we analyzed review data through text mining like sentiment analysis and topic modeling analysis method based on previous research analysis. Findings The results showed that Chinese tourists gave higher ratings and relatively less negative ratings than American tourists. And American tourists have more negative sentiments and emotions in writing online reviews than Chinese tourists. Also, through the analysis results using topic modeling, it was confirmed that Chinese tourists mentioned more topics about the hotel location, room, and price, while American tourists mentioned more topics about hotel service. American tourists also mention more topics about hotels than Chinese tourists, indicating that American tourists tend to provide more information through online reviews.

텍스트 마이닝을 활용한 캡스톤 디자인에 관한 학생 인식 탐색: 산업경영공학 사례 (A Text Mining Analysis on Students' Perceptions about Capstone Design: Case of Industrial & Management Engineering)

  • 위광호;김윤진;김문수
    • 공학교육연구
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    • 제25권5호
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    • pp.85-93
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    • 2022
  • Capstone Design, a project-based learning technique, is the most important curriculum that clarifying major knowledge and cultivating the ability to apply through the process of solving problems in the industrial field centered on the student project team. Accordingly, various and extensive studies are being conducted for the successful implementation of capstone design courses. Unlike previous studies, this study aimed to quantitatively analyze the opinions that recorded the experiences and feelings of students who performed capstone design, and used text mining methodologies such as frequency analysis, correlation analysis, topic modeling, and sentiment analysis. As a result of examining the overall opinions of the latter period through frequency analysis and correlation analysis, there was a difference between the languages used by the students in the opinions according to gender and project results. Through topic modeling analysis, 'topic selection' and 'the relationship between team members' showed an increase in occupancy or high occupancy, and topics such as 'presentation', 'leadership', and 'feeling what they felt' showed a tendency to decreasing occupancy. Lastly, sentiment analysis has found that female students showed more neutral emotions than male students, and the passed group showed more negative emotions than the non-passed group and less neutral emotions. Based on these findings, students' practical recognition of the curriculum was considered and implications for the improvement of capstone design were presented.

Qualitative Research in Healthcare: Necessity and Characteristics

  • Jeehee Pyo;Won Lee;Eun Young Choi;Seung Gyeong Jang;Minsu Ock
    • Journal of Preventive Medicine and Public Health
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    • 제56권1호
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    • pp.12-20
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    • 2023
  • Quantitative and qualitative research explore various social phenomena using different methods. However, there has been a tendency to treat quantitative studies using complicated statistical techniques as more scientific and superior, whereas relatively few qualitative studies have been conducted in the medical and healthcare fields. This review aimed to provide a proper understanding of qualitative research. This review examined the characteristics of quantitative and qualitative research to help researchers select the appropriate qualitative research methodology. Qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions. Qualitative research is conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants and data collection methods, (5) data analysis and description of findings, and (6) research validation. This review can contribute to the more active use of qualitative research in healthcare, and the findings are expected to instill a proper understanding of qualitative research in researchers who review qualitative research reports and papers.

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

  • 김지영;노동조
    • 한국비블리아학회지
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    • 제34권4호
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    • pp.207-234
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    • 2023
  • 4차 산업혁명이 등장한 이래로 산업 분야를 비롯한 다양한 분야에서 관련 연구들이 수행되었다. 본 연구에서는 4차 산업혁명에 대한 국내의 연구 동향을 분석하기 위하여 2016년 1월부터 2023년 8월까지 KCI에 수록된 2,115건의 논문을 대상으로 핵심어 분석 및 LDA 알고리즘에 기반한 토픽모델링 분석을 실시하였다. 본 연구의 결과 첫째, 4차 산업혁명 관련 학술 논문이 많이 게재된 학술지는 디지털융복합연구, 인문사회 21, e-비즈니스연구, 학습자중심교과교육연구 등의 순이었다. 둘째, 토픽모델링 분석 결과, '인간과 인공지능', '데이터와 개인정보 관리', '교육과정의 변화', '기업의 변화와 혁신', '교육의 변화와 일자리', '문화예술과 콘텐츠', '정보와 기업의 정책과 대응'의 7개 토픽이 선정되었다. 셋째, 4차 산업혁명과 관련한 공통 연구주제는 '교육과정의 변화', '인간과 인공지능', '문화예술과 콘텐츠'이며, 공통 키워드는 '기업', '정보', '보호', '스마트', '시스템' 등이 있다. 넷째, 연구 전반기(2016-2019)에는 교육 분야의 주제가 상위에 등장했으나 후반기(2020-2023)에는 기업과 스마트, 디지털, 서비스 혁신에 관한 주제들이 상위로 나타났다. 다섯째, 연구 후반기로 가면서 연구 주제들이 보다 구체화되거나 세분화되는 경향을 보였다. 이러한 동향은 코로나 팬데믹 이후 4차 산업혁명 분야의 핵심 기술들이 다양한 산업 분야에 활용됨에 따라 발생하는 사회경제적 변화에 따른 것으로 해석된다. 본 연구의 결과는 4차 산업혁명 분야의 연구 동향 파악과 전략 수립 및 후속 연구에 유용한 정보를 제공할 수 있을 것으로 기대한다.

코로나19 관련 키워드 분석: 토픽 모델링과 의미 연결망 네트워크 분석을 중심으로 (COVID19 Related Keyword Analysis: Based on Topic Modeling and Semantic Network Analysis)

  • 김동욱;이민상;정재영;김현철
    • 반도체디스플레이기술학회지
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    • 제21권2호
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    • pp.127-132
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    • 2022
  • In the era of COVID-19 pandemic, COVID related keywords, news and SNS data are pouring out. With the help of the data and LDA topic modeling, we can check out what media reports about COVID-19 and vaccines. Also, we can be clear how the public reacts to the vaccine on social media and how this is related with the increasing number of COVID-19 patients. By using sentimental analysis methodology, we can get to know about the different kinds of reports that Korea media send out and get to know what kind of emotions that each media company uses in majority. Through this procedure, we can know the difference between the Korean media and the foreign ones. Ultimately, we can find and analyze the keyword that suddenly rose during the COVID-19 period throughout this research.

텍스트 분석을 통한 제품 분류 체계 수립방안: 관광분야 App을 중심으로 (Building a Hierarchy of Product Categories through Text Analysis of Product Description)

  • 임현아;최재원;이홍주
    • 지식경영연구
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    • 제20권3호
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    • pp.139-154
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    • 2019
  • With the increasing use of smartphone apps, many apps are coming out in various fields. In order to analyze the current status and trends of apps in a specific field, it is necessary to establish a classification scheme. Various schemes considering users' behavior and characteristics of apps have been proposed, but there is a problem in that many apps are released and a fixed classification scheme must be updated according to the passage of time. Although it is necessary to consider many aspects in establishing classification scheme, it is possible to grasp the trend of the app through the proposal of a classification scheme according to the characteristic of the app. This research proposes a method of establishing an app classification scheme through the description of the app written by the app developers. For this purpose, we collected explanations about apps in the tourism field and identified major categories through topic modeling. Using only the apps corresponding to the topic, we construct a network of words contained in the explanatory text and identify subcategories based on the networks of words. Six topics were selected, and Clauset Newman Moore algorithm was applied to each topic to identify subcategories. Four or five subcategories were identified for each topic.