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

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.97-122
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• 2023

Metaliteracy is a new framework that reframes information literacy. Metaliteracy is distinguished from information literacy through the intruduction of postmodernism, social constructivism and metacognition. However it has been not examined whether metaliteracy studies reflect the conceptual differences. Therefore, The purpose of the study is to observe research trends of metaliteracy on the difference from information literacy. In the study, literature reviews were conducted, and frequency analysis and knowledge network analysis(co-occurrence and bibliographic coupling) were conducted for 80 metaliteracy studies. The results of the study are as follows. As a result of co-occurrence analysis, metacognition(frequency 1st) and skills(degree centrality 1st, closeness centrality 1st, betweenness centrality 1st) appeared. Since metaliteracy criticizes skill-based information literacy, the result suggests that the concepts of information literacy and metaliteracy are mixed. On the other hand, as a result of bibliographic coupling analysis, studies with high bibliographic coupling explain the difference between information literacy and metaliteracy through metacognition.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.21-31
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• 2013

ECU(Electric Control Unit) on the important features of the vehicle is equipped, ECU between sending and receiving messages is connected to one of the internal network(CAN BUS), but this network easily accessible from the outside and not intended to be able to receive attacks from an attacker, In this regard, the development of tools that can be used in order to verify the possibility of attacks on attacks from outside, However, the time costs incurred for developing tools and time to analyze from actual car for CAN messages to be used in the attack to find. In this paper, we want to solve it, propose a method to generate test cases required for the attack is publicly available tool called Sulley and it explains how to find the CAN messages to be used in the attack. Sulley add the CAN messages data generated library files in provided library file and than Sulley execute that make define and execute file conform to the CAN communication preferences and create message rules. Experiments performed by the proposed methodology is applied to the actual car and result, test cases generated by the CAN messages fuzzing through Sulley send in the car and as a result without a separate tool developed was operating the car.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.2
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• pp.353-378
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• 2014

The purpose of this study is to find factors to affect on the formation of semantic relation from terminology and what is to be affected by these factors to build the database scheme of terminology dictionary by a structural definition. In this research, 826,905 keywords of 88,874 social science articles and 985,580 keywords of 125,046 humanities science articles in the KCI journals from 2007 to 2011 were collected. From collected data, subject complexity, structural hole, term frequency, occurrence pattern and an effect between the number of nodes and the number of patterns which were derived from the semantic relation of linked terms of established 'STNet' System were analyzed. The summarized results from analyzed data and network patterns are as follows. Betweenness Centrality, term frequency, and effective size affect the numbers of semantic relation node. Among these factors, betweenness centrality was the most effective and effective size. But term frequency was the least effective. Betweenness Centrality, term frequency, and effective size affect the numbers of semantic relation type. Term frequency is the most effective. Therefore, when building a terminology dictionary, factors of betweenness centrality, term frequency, effective size, and complexity of subject are needed to select term. As a result, these factors can be expected to improve the quality of terminology dictionary.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.289-307
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• 2016

Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.341-357
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• 2018

Due to the paradigm of open science and advanced digital information technology, data sharing and re-use have been actively conducted and considered data-intensive in a wide variety of disciplines. This study aims to investigate the intellectual structure portrayed by the research products re-using the data sets from ICPSR. For the purpose of this study, a total of 570 research products published in 2017 from the ICPSR site were collected and analyzed in two folds. First, the authors and publications of those research products were analyzed in order to show the trends of research using ICPSR data. Authors tend to be affiliated with university or research institute in the United States. The subject areas of journals are recognized into Social Sciences, Health, and Psychology. In addition, a network with clustering analysis was conducted with using co-word occurrence from the titles of the research products. The results show that there are 12 clusters, mental health, tabocco effect, disorder in school, childhood, and adolescence, sexual risk, child injuries, physical activity, violent behavior, survey, family role, women, problem behavior, gender differences in research areas. The structure portrayed by ICPSR data re-uses demonstrates that substantial number of studies in Medicine have been conducted with a perspective of social sciences.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.2
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• pp.189-209
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• 2019

Main Path Analysis (MPA) is one of the text mining techniques that extracts the core literature that contributes knowledge transfer based on citation information in the literature. This study applied various text mining techniques to abstract of the paper related with sense-of-place, which is published at Korea and abroad from 1990 to 2018 so that could discuss in a macro perspective. The main path analysis results showed that from 1990, overseas research on sense-of-place has been carried out in the order of personal identity, public land management, environmental education and urban development-related areas. Also, by using the network analysis, this study found that sense-of-place was discussed at various levels in Korea, including urban development, culture, literature, and history. On the other hand, it has been found that there are few topic changes in international studies, and that discussions on health, identity, landscape and urban development have been going on steadily since the 1990s. This study has implications that it presents a new perspective of grasping the overall flow of relevant research.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.451-458
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• 2022

This article is devoted to the problem of national and patriotic education of young students by means of digital technologies in the conditions of distance learning environment. It is emphasized that national and patriotic education is a powerful means of strengthening the unity and integrity of Ukraine. It is proved that national and patriotic education will be effective under the condition of systematic and purposeful activity on formation of patriotic consciousness in youth, sense of national dignity, necessity of service of ideals and values of the country. Various forms of educational work of national and patriotic orientation at Pavlo Tychyna Uman State Pedagogical University, which were conducted by digital technologies: online thematic lectures, educational classes, round tables, workshops, guest online meetings with famous researchers of historical heritage of Ukraine, online tours of historical places, virtual exhibitions of art, participation in the national-patriotic student camp "Diia" (Action) and etc. The activity of the University Library and V. O. Sukhomlinsky State Scientific and Pedagogical Library of Ukraine of the National Academy of Pedagogical Sciences of Ukraine, which has a significant impact on the formation of national consciousness and social and political activity of students by modern means of information and communication technologies. It is determined that the project "Inclusive 3D map" helps to broaden the horizons and deepen the knowledge of young students, education of a true citizen, the formation of cognitive interest in the subjects studied, motivation to study, raising awareness of Ukrainians on historical and cultural heritage. The study showed that young students take an active social attitude: they speak Ukrainian, want to live and work in Ukraine, respect their homeland, its traditions, cultural and historical past, love to travel and they are tolerant of people with special needs. Promising areas of educational work with students based on the use of a wide range of information and communication technologies, namely 3D games, TV tandems, podcasts, social networks, video resources in national and patriotic education of youth.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.241-264
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• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• 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.