• Journal of the Korean Society for information Management
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• v.41 no.2
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• pp.295-316
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• 2024

Analyzing research trends is essential for the sustainable development of a discipline and is important for understanding the value of prior research and laying the groundwork for subsequent research. This study aims to draw implications for the future direction of convergence research on the disclosure of information from various disciplines by comparing and analyzing the trends in disclosure of information research in Korea. For this purpose, we analyzed the publication frequency of information disclosure papers listed in the Korea Citation Index (KCI) from 2002 to 2023 and the publication trend by discipline as a time series. In addition, we compared the keyword relationships and specialized research topics of each discipline by applying network analysis and LDA topic modeling techniques to the names and keywords of papers in law, public administration, and library and information science. As a result of the analysis, the law focuses on legal regulations and policy improvement, public administration focuses on changing social needs and administrative operation methods, and LIS focuses on practical approaches to record management and disclosure of information. Based on this, future research directions include combining policy research in law with social change research in public administration and developing realistic policies and operational guidelines from the practical perspective of LIS. Such convergent research will enable the systematic and efficient implementation of disclosure of information systems, contributing to the guarantee of the public's right to know and the enhancement of state transparency.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.204-209
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• 2023

Dynamic Bandwidth Allocation (DBA) methods in telecommunication network & systems have emerged with mechanisms for sharing limited resources in a rapidly growing number of users in today's access networks. Since the DBA research trends are incredibly fast-changing literature where almost every day new areas and terms continue to emerge. Co - citation analysis offers a significant support to researchers to distinguish intellectual bases and potentially leading edges of a specific field. We present the visualization based analysis for DBA algorithms in telecommunication field using mainstream co-citation analysis tool-CiteSpace and web of science (WoS) analysis. Research records for the period of decade (2009-2018) for this analysis are sought from WoS. The visualization results identify the most influential DBA algorithms research studies, journals, major countries, institutions, and researchers, and indicate the intellectual bases and focus entirely on DBA algorithms in the literature, offering guidance to interested researchers on more study of DBA algorithms.

• Journal of the Korean Society for information Management
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• v.28 no.4
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• pp.7-31
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• 2011

The aims of this study are to provide an overview of research trends on user interface in the field of Information Science. This study attempts to address the following four questions: 1) what are the research areas or subject topics, 2) what are the patterns of user interface publication, 3) what methods are often used to what topics, and 4) what are the changes in the subject topics and research methods over the past ten years. It analyzed a total of 128 research articles published in four Korean LIS journals and one U.S. journal. The study also reviewed 72 articles published in Korean journals for identifying research trends. The study found that the most productive areas were 'web site evaluation', followed by 'search interface', 'information design' and 'interaction style design'. The most frequently used research methods were survey methods, followed by unobtrusive methods, and experiments. Journal of the Korean Society for Information Management published the most articles on research of user interface. The research of user interface was conducted more frequently in the early 2000s than later years.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.351-379
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• 2023

The goal of this study is to investigate the domestic and international research trends on metaverse related researches. To achieve this goal, a set of 913 journal articles were collected from KCI (Korea Citation Index), 232 articles from WoS (Web of Science), and 277 articles from WoS-CPCI (Conference Proceeding Citation Index). A descriptive analysis shows the number of researches has been increased radically, and the mostly researched subject areas are interdisciplinary, computer science, and education in KCI, business and economics in WoS, and computer science in WoS-CPCI. The co-occurrence network analysis using author keywords revealed that technology related terms such as virtual reality and augmented reality showed high centrality measures in all of the databases, and the cluster analysis resulted in education and metaverse platform related keywords cluster from KCI, bibliometric analysis related keywords cluster from WoS, and all the metaverse technology related keywords cluster from WoS-CPCI.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.81-83
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• 2022

Understanding research trends is necessary to select research topics and explore related works. Most researchers search representative keywords of interesting domains or technologies to understand research trends. However some conferences in artificial intelligence or data mining fields recently publish hundreds to thousands of papers for each year. It makes difficult for researchers to understand research trend of interesting domains. In our paper, we propose an automatic technology keyphrase extraction method to support researcher to understand research trend for each conference or journal. Keyphrase extraction that extracts important terms or phrases from a text, is a fundamental technology for a natural language processing such as summarization or searching, etc. Previous keyphrase extraction technologies based on pretrained language model extract keyphrases from long texts so performances are degraded in short texts like titles of papers. In this paper, we propose a techonolgy keyphrase extraction model that is robust in short text and considers the importance of the word.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.126-136
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• 2020

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.6-19
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• 2019

The purpose of this article is to problematize the existence of a possible Ibero-American informational thinking. It was initially observed that a relative absence of Ibero-America in the international presentations and mappings of information science exists. Below, the reality of the 22 countries that compose Ibero-America is discussed, a region that can be understood from a sociocultural and geopolitical perspective. Then, a mapping of the information science research in these countries is made. The main research topics found are: epistemological studies, relationships with library science, information literacy, representation and organization, bibliometric studies, information management, user studies, technological dimensions, and relationships with archival science and museum studies. Finally, a general epistemological configuration of information science is presented at a global level, highlighting the great trends of study of information that marked the decades of the 1960s and 1970s (physical model), 1980s and 1990s (cognitive model), and the 21st century (sociocultural model), and which manifested themselves in the different subareas that make up the field. The most recent research in information science, in addition to addressing information transfer (physical dimension) and its relationship with data and knowledge (cognitive dimension), has also incorporated aspects related to the social effects of information, its role in the constitution of identities and culture, and the importance of its material conformations. Such expansion reflects attempts to address the complexity of informational phenomena. Therefore, it is concluded that it is important to place the specific contributions of Ibero-America in this context.

• Journal of Korean Library and Information Science Society
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• v.48 no.1
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• pp.373-396
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• 2017

The purpose of this study was to examine the trends of qualitative research in four representative journals in Korean LIS from 1970 to 2016. 73 papers(1.4%) were analyzed focusing on publication year, subject areas, research purposes, authors, qualitative methods, research participants, data collection methods, data analysis methods, and methods of validation. The findings are as follows: 1) Information behaviour(39.7%) was the most researched topics, followed by librarians work(20.5%), and bibliotherapy & reading education(13.6%). 2) The most frequently used research purpose was for understanding experiences(60.2%) and for improving current state(30.1%). 3) 'Grounded theory'(13.6%) and 'phenomenology'(10.9%), 'case study'(10.9%), were used frequently, while 'non-specified qualitative method' was 26.0% and 'not indicated' was 21.9%. 4) Librarians (41.0%) were the most researched participants, followed by professionals(13.6%). To collect qualitative data, in-depth interview(20.5%), interview(13.6%), and in-depth interview & internal documents(9.5%) were frequently used. There are 'loose qualitative research' group and 'scientific qualitative research' group. LIS researchers using qualitative research methods should consistently make efforts to increase qualitative theory and the philosophical assumptions, and to apply rigorous research method (data collection, analysis and interpretation, sampling, data saturation, validity and reliability). Institutionally, It is to provide 'qualitative research methods' course and to develop guidelines and standards for LIS qualitative research authors and reviewers.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.141-148
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• 2016

In this paper, we propose a topic network analysis approach which integrates topic modeling and social network analysis. We collected 2,039 scientific papers from five top journals in the field of data mining published from 1996 to 2015, and analyzed them with the proposed approach. To identify topic trends, time-series analysis of topic network is performed based on 4 intervals. Our experimental results show centralization of the topic network has the highest score from 1996 to 2000, and decreases for next 5 years and increases again. For last 5 years, centralization of the degree centrality increases, while centralization of the betweenness centrality and closeness centrality decreases again. Also, clustering is identified as the most interrelated topic among other topics. Topics with the highest degree centrality evolves clustering, web applications, clustering and dimensionality reduction according to time. Our approach extracts the interrelationships of topics, which cannot be detected with conventional topic modeling approaches, and provides topical trends of data mining research fields.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.1
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• pp.25-44
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• 2013

The purpose of this study was to analyze the trends of Classification Studies in Korea from 205 research articles in five scholarly journals in Library and Information Science during the period 1986-2011. Individual article was analyzed in the aspects of specific research topics, research methodologies, data collection & analysis, and the characteristics of classification research was suggested. The amount of research paper has increased during the period and the focus of the study was on practical use and most of the papers were about new classification schedules or modification of current classification systems. Most of the papers were literature research and comparative research on classification systems by professors or graduate students. Top 9 authors in classification research were professors or lecturers and a few authors were computer science major. Therefore, various research topics, research methodologies and collaborations with other disciplines are necessary for future classification research.