• Title/Summary/Keyword: Keyword Co-occurrence Network

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Analysis of University Unification Education Research Trends Using Text Network Analysis and Topic Modeling

  • Do-Young LEE
    • Journal of Wellbeing Management and Applied Psychology
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    • v.6 no.4
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    • pp.27-31
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    • 2023
  • Purpose: This study analyzed papers identified by entering the two keywords 'unification education' and 'university' during research from 2013 to 2022 in order to identify trends and key concepts in unification education research at domestic universities. Research design, data, and methodology: The study analyzed 224 papers, excluding those on primary, middle, and high school unification education, as well as unrelated and duplicate papers. The analysis included developing a co-occurrence network of keywords, utilizing topic modeling to categorize research types, and confirming visualizations such as word clouds and sociograms. Results: In the final analysis, the research identified 1,500 keywords, with notable ones like 'Korea,' 'education,' 'unification.' Centrality analysis, measuring influence through connected keywords, revealed that 'Korea,' 'education,' 'north,' and 'unification' held significant positions. Keywords with high centrality compared to their frequency included 'learning,' 'development,' 'training,' 'peace,' and 'language,' in that order. Conclusions: This study investigated trends and structures in university-level unification education by analyzing papers identified with the keywords 'unification education' and 'university.' The use of keyword network analysis aimed to elucidate patterns and structures in university-level unification education. The significance of the study lies in offering foundational data for future research directions in the field of unification education at universities.

Microplastics Intellectual Network Analysis based on Bigdata (빅데이터 기반한 미세플라스틱 지적네트워크 분석)

  • Kim, Younghee;Chang, Kwanjong
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.239-259
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    • 2022
  • Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

Bibliometric analysis of source memory in human episodic memory research (계량서지학 방법론을 활용한 출처기억 연구분석: 인간 일화기억 연구를 중심으로)

  • Bak, Yunjin;Yu, Sumin;Nah, Yoonjin;Han, Sanghoon
    • Korean Journal of Cognitive Science
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    • v.33 no.1
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    • pp.23-50
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    • 2022
  • Source memory is a cognitive process that combines the representation of the origin of the episodic experience with an item. By studying this daily process, researchers have made fundamental discoveries that make up the foundation of brain and behavior research, such as executive function and binding. In this paper, we review and conduct a bibliometric analysis on source memory papers published from 1989 to 2020. This review is based on keyword co-occurrence networks and author citation networks, providing an in-depth overview of the development of source memory research and future directions. This bibliometric analysis discovers a change in the research trends: while research prior to 2010 focused on individuality of source memory as a cognitive function, more recent papers focus more on the implication of source memory as it pertains to connectivity between disparate brain regions and to social neuroscience. Keyword network analysis shows that aging and executive function are continued topics of interest, although frameworks in which they are viewed have shifted to include developmental psychology and meta memory. The use of theories and models provided by source memory research seem essential for the future development of cognitive enhancement tools within and outside of the field of Psychology.

Investigating Topics of Incivility Related to COVID-19 on Twitter: Analysis of Targets and Keywords of Hate Speech (트위터에서의 COVID-19와 관련된 반시민성 주제 탐색: 혐오 대상 및 키워드 분석)

  • Kim, Kyuli;Oh, Chanhee;Zhu, Yongjun
    • Journal of the Korean Society for information Management
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    • v.39 no.1
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    • pp.331-350
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    • 2022
  • This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.

Analysis on Topics of Digital Preservation Researches and Courses (디지털 보존 관련 학술연구 및 교과 주제분석)

  • Jeong, Uiyeon;Choi, Sanghee
    • Journal of the Korean Society for Library and Information Science
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    • v.53 no.3
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    • pp.25-43
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    • 2019
  • Recently there has been a growing interest in digital preservation and digital curation with rapid increase of digital resource. This study aims to investigate the research topics and the course topics related digital preservation and digital curation. The course information is collected from the curricular of library and information science departments and archival science departments in leading countries such as US, England, Ireland, Canada and New Zealand. Title keyword profiling and network analysis were adapted to discover core research and education areas. The key topics in the abstracts of research papers and the contents of the course were also illustrated by these methods. In the research analysis, archival system is the biggest area of researches related digital preservation and digital curation. Courser analysis shows digital curation education and process is the important area of education. As a result of content analysis, plan and strategy is a notable topic of research and record management process is a major topic of courses for digital preservation and digital curation. In addition, format of digital resource is an important topic for research and courses.

Knowledge Visualization and Mapping of Studies on Social Systems Theory in Social Sciences: Focused on Niklas Luhmann (사회과학 분야 사회적 체계 이론 연구의 지식 시각화와 매핑 - Niklas Luhmann을 중심으로 -)

  • Park, Seongwoo;Hong, Soram
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.1
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    • pp.253-275
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    • 2022
  • Niklas Luhmann is one of the most contentious and difficult theorist in sociology but follow-up studies on his theory gradually increase for recent 10 years. The purpose of this study is to observe how follow-up studies use the difficult concepts of Luhmann. Unlike previous studies, this study adopted a keyword rather than an article as the unit of analysis because keywords are linguistic constructs that can make concepts observable. The study analyzed co-occurrence of keywords in 139 articles retrieved from social sciences category in Web of Science DB. The key findings were following: the most important keywords were the name of Luhmann(Niklas Luhmann) and theory(social systems); keywords were grouped into 4 clusters(social systems theory, systems theory, legal system and political system, the significant of Luhmann's theory from the viewpoint of the history of social theory); topic terms were systems theory, communication, Autopoiesis, risk, legal system, functional differentiation, environment, social theory, sociological theory, structural coupling, systems and evolution. The significance of the study is following: the study gives keywords as useful access point for beginners of Luhmann's theory; the study proves that content analysis by keywords network can be applied to trend analysis of difficult theoretical researches.

Developing a Classification of Vulnerabilities for Smart Factory in SMEs: Focused on Industrial Control Systems (중소기업용 스마트팩토리 보안 취약점 분류체계 개발: 산업제어시스템 중심으로)

  • Jeong, Jae-Hoon;Kim, Tae-Sung
    • Journal of Information Technology Services
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    • v.21 no.5
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    • pp.65-79
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    • 2022
  • The smart factory has spread to small and mid-size enterprises (SMEs) under the leadership of the government. Smart factory consists of a work area, an operation management area, and an industrial control system (ICS) area. However, each site is combined with the IT system for reasons such as the convenience of work. As a result, various breaches could occur due to the weakness of the IT system. This study seeks to discover the items and vulnerabilities that SMEs who have difficulties in information security due to technology limitations, human resources, and budget should first diagnose and check. First, to compare the existing domestic and foreign smart factory vulnerability classification systems and improve the current classification system, the latest smart factory vulnerability information is collected from NVD, CISA, and OWASP. Then, significant keywords are extracted from pre-processing, co-occurrence network analysis is performed, and the relationship between each keyword and vulnerability is discovered. Finally, the improvement points of the classification system are derived by mapping it to the existing classification system. Therefore, configuration and maintenance, communication and network, and software development were the items to be diagnosed and checked first, and vulnerabilities were denial of service (DoS), lack of integrity checking for communications, inadequate authentication, privileges, and access control in software in descending order of importance.

Perceptions of Disabled Sports in Newspapers Using Semantic Networks Analysis (신문기사에 나타난 장애인스포츠에 대한 인식 -의미연결망을 활용한 빅데이터 분석-)

  • Han, Min-kyu;Kim, Won-Kyoung;Yoon, Jiwun
    • 재활복지
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    • v.20 no.4
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    • pp.157-175
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    • 2016
  • The purpose of this study was to analyze the perceptions of disabled sports that were reported the newspapers using semantic network analysis method. for this purpose, 745 news articles were selected from 21 source in Naver news searching engine. The main keyword for searching on newspapers was 'disabled sports'. Krkwic software was used for keyword cleansing and co-occurrence of text to text matrix in frequencies. Centrality indices that are degree, between and eigenvector, were used to analyze the perceptions of disabled sports from Netminer 4.0 for semantic network analysis. The conclusion of overall results from this study are follows; First, the core keyword of disabled sports in newspapers are 'impression', 'challenge', 'festival', 'dream' and hope. And there is different concepts of cognition among types of disability. Second, there are two elements on the perceptions of disabled sports from reported newspapers; sports performance and emotional. Specifically, main stream of keyword were 'Paralympics' and 'Special Olympics' on sports performance element and 'impressive' and 'challenge' in emotion element.

A Technical Approach for Suggesting Research Directions in Telecommunications Policy

  • Oh, Junseok;Lee, Bong Gyou
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.12
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    • pp.4467-4488
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    • 2014
  • The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

A Comparative Analysis Study of IFLA School Library Guidelines Using Semantic Network Analysis (언어 네트워크 분석을 통한 IFLA의 학교도서관 가이드라인 비교·분석에 관한 연구)

  • Lee, Byeong-Kee
    • Journal of Korean Library and Information Science Society
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    • v.51 no.2
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    • pp.1-21
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    • 2020
  • The purpose of this study is to explore semantic characteristics of IFLA school library guidelines through network analysis. There are two versions, 2002 edition and 2015 revision of the guidelines. This study analyzed the 2002 edition and 2015 revision of the IFLA school library guidelines view point of semantic network, and compared characteristics of two versions. The keywords were to extracted from two texts, semantic network were composed based on co-occurrence relations with keywords. The centrality(degree centrality, closeness centrality, betweenness centrality) was analyzed from the network. In addition, this study conducted topic modeling analysis using LDA function of NetMiner4.0. The result of this study is following these. First, When comparing the centrality, the 'Program, Teaching, Reading, Inquiry, Literacy, Media' keyword was higher in the 2015 revision than in the 2002 edition. Second, 'Inquiry' in degree centrality and 'Achievement' in closeness centrality which were not included in the 2002 edition top-ranked keyword list, have new appeared in 2015 revision. third, As a result of the analysis of topic modeling, compared to the 2002 version, the importance of topics on programs and services, teaching and learning activities of librarian teacher, and media and information literacy is increasing in the 2015 revision.