• Journal of the Korean Society for Library and Information Science
• /
• v.54 no.2
• /
• pp.197-223
• /
• 2020

In this study, citation-weighted author profiling (CWAP) was developed as a new method that combines the advantages of both author profiling (AP) method and author co-citation analysis (ACA) method. In AP method, words reflect the author's main topics of study. On the other hand, what words reflect in CWAP is topics that the author mainly influences. This enables detailed topic identification, which is the advantage of AP method, and at the same time determines the subjects in which the author has influence, as with ACA method. The proposed CWAP method was applied experimentally to analyze the intellectual structure of school library research in Korea. The results of the trial application revealed in detail what topics each author has a high influence on, and the change of influence over time was also clearly revealed. The CWAP method proposed in this study is expected to be used as a technique to grasp detailed topics from the viewpoint of research influence on which topics the author has been cited for, not as a research productivity perspective of how many papers the author has published.

• Journal of the Korean Society for Library and Information Science
• /
• v.53 no.3
• /
• pp.25-43
• /
• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.3
• /
• pp.137-147
• /
• 2022

Diagnosis and management of skin condition is a very basic and important function in performing its role for workers in the beauty industry and cosmetics industry. For accurate skin condition diagnosis and management, it is necessary to understand the skin condition and needs of customers. In this paper, we developed SCIS, a big data-based skin care information system that supports skin condition diagnosis and management using social media big data for skin condition diagnosis and management. By using the developed system, it is possible to analyze and extract core information for skin condition diagnosis and management based on text information. The skin care information system SCIS developed in this paper consists of big data collection stage, text preprocessing stage, image preprocessing stage, and text word analysis stage. SCIS collected big data necessary for skin diagnosis and management, and extracted key words and topics from text information through simple frequency analysis, relative frequency analysis, co-occurrence analysis, and correlation analysis of key words. In addition, by analyzing the extracted key words and information and performing various visualization processes such as scatter plot, NetworkX, t-SNE, and clustering, it can be used efficiently in diagnosing and managing skin conditions.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.26 no.4
• /
• pp.245-262
• /
• 2015

As the topics of general education in universities become more diverse, it is not an easy task to identify the topics of general education courses. This study aims to identify and visualize the topics of A university's general education courses using informetric analysis methods. 214 syllabi were collected and titles, course introduction, goals, and weekly plans were analyzed. 278 topic words were extracted from the data set and grouped into 8 clusters. In the network analysis, topic clusters were divided into two areas, personal and social. Personal area has 14 sub-topic clusters and social area has 11 sub-topic clusters. In personal area, 'language', 'science', and 'personality' were major topic clusters. In social area, 'multi-culture' cluster was the core cluster with connected to four other clusters. The topic network generated in this study can be used for the university and the university library to enhance general education or to develop collections for general education.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.107-132
• /
• 2024

This study attempted to analyze newspaper articles related to May 18 through frequency analysis and network analysis using news data related to May 18 for about 30 years from 1990 to 2022 at the Korea Press Foundation's Big Kinds. Specifically, quantitative change trends were examined by analyzing the amount of articles by period and region, and the connection structure between major keywords by the regime was explored through network analysis by regime using co-appearance keywords. As a result of the analysis, it was found that 2019 had the largest amount of coverage, which had many social issues in time, and the Jeolla-do region had the largest amount of coverage in the region. And as a result of network analysis, there were differences in words related to May 18 in news data according to the perception and policy of the regime toward May 18. As a result of synthesizing the analysis of May 18 news data, it was confirmed that May 18 was becoming a democratic movement over time regardless of region, but at the same time, the distortion of May 18 was not resolved.

• Journal of the Korean Society for Library and Information Science
• /
• v.55 no.2
• /
• pp.147-178
• /
• 2021

In this study, co-word analysis was conducted to investigate the intellectual structure of the domestic open access area. Through KCI and RISS, 124 research articles related to open access in Korea were selected for analysis, and a total of 1,157 keywords were extracted from the title and abstract. Network analysis was performed on the selected keywords. As a result, 3 domains and 20 clusters were extracted, and intellectual relations among keywords from open access area were visualized through PFnet. The centrality analysis of weighted networks was used to identify the core keywords in this area. Finally, 5 clusters from cluster analysis were displayed on a multidimensional scaling map, and the intellectual structure was proposed based on the correlation between keywords. The results of this study can visually identify and can be used as basic data for predicting the future direction of open access research in Korea.

• The Journal of the Korea Contents Association
• /
• v.21 no.10
• /
• pp.21-37
• /
• 2021

This study investigated the intellectual structure of the latest trends in Korean addiction research in the social sciences. A network analysis of keywords with co-word occurrence was performed on 172 papers from the KCI database based on the data from the year of 2019, and a total of 432 keywords were extracted. The network analysis was performed using several programs: Bibexcel, COOC, WNET, and NodeXL. As a result of the study, keywords related to addiction type, study subjects, research methods, and research variables were found, and a total of 20 clusters were identified. Furthermore, to identify and measure weighted networks, the relationships between each keyword were explored and discussed in detail through a network analysis of global centralities, local centralities, and betweenness centralities. The study indicated that the latest issues were focused on smartphone addiction and provided implications for the future research and practice that fields and topics of relationship addiction, food addiction, and work addiction should be more considered. Further, the study discussed the relationship between drug addiction-crime, alcohol addiction-family, and gambling addiction-motivation and the necessity of qualitative study.

• Korean Journal of Cognitive Science
• /
• v.33 no.1
• /
• pp.23-50
• /
• 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.

• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.92-104
• /
• 2021

This study aims to analyze online news articles to identify social issues related to patient safety and compare the changes in these issues before and after the implementation of the Patient Safety Act. This study performed text mining through the R program, wherein 7,600 online news articles were collected from January 1, 2010, to March 5, 2020, and examined using keyword analysis, topic modeling, and word co-occurrence network analysis. A total of 2,609 keywords were categorized into 8 topics: "medical practice", "medical personnel", "infection and facilities", "comprehensive nursing service", "medicine and medical supplies", "system development and establishment for improvement", "Patient Safety Act" and "healthcare accreditation". The study revealed that keywords such as "patient safety awareness", "infection control" and "healthcare accreditation" appeared before the implementation of the Patient Safety Act. Meanwhile, keywords such as "patient safety culture". and "administration and injection" appeared after the act's implementation with improved ranking of importance pertaining to nursing-related terminology. Interest in patient safety has increased in the medical community as well as among the public. In particular, nursing plays an important role in improving patient safety. Therefore, the recognition of patient safety as a core competency of nursing and the persistent education of the public are vital and inevitable.

• Journal of Information Technology Applications and Management
• /
• v.19 no.4
• /
• pp.1-18
• /
• 2012

This paper identifies technology trends of national research and development (national R&D) by exploiting Korean national R&D patents, ranging from 2007 to 2010. In this paper, co-word analysis (CWA), which is a method to identify the relationship among technology terms by using their co-occurrences, is incorporated into network analysis to visualize the relationships among technology keywords of national R&D patents and calculate network indexes concerning inter-relationship diversity and strength of technology keywords. As a result, this research found that inter-relationship among technology keywords in national R&D are getting increasingly strengthening in an overall sense. In addition, the keyword inter-relationship diversity-strength map proposed in this paper revealed some significant technological keywords of national R&D : core technology keywords including "sensor", "film" and "fuel" and emerging keywords including "biosensor" and "thermoelectric". Because the proposed approach helps identify interdisciplinary trends of technology keywords from a massive volume of national R&D patents in a visual and quantitative way, we expect that the approach can be incorporated as a preliminary into the R&D planning process to assist R&D policy makers to understand technology convergence of national R&D and develop relevant R&D policies.