• Journal of Korea Trade
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• v.24 no.8
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• pp.171-188
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• 2020

Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

• 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.

• Asia Marketing Journal
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• v.11 no.2
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• pp.73-96
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• 2009

In this paper, authors focused on the difference between successful and unsuccessful items in terms of the innovation and imitation parameters of Bass diffusion model. Each item was scraped by members directly from the minihompies they visit. Top 50 items in terms of total number of adoption are classified as successful items and the 50 items whose total number of adoption was just below the average are classified as unsuccessful items. In particular, authors are interested in investigating the role of influentials in the diffusion process. Influentials are defined as those people whose network centrality (Indegree, Outdegree, and Betweeness centrality) was larger than the mean centrality in their social network. Figure 1 shows the plots of number of scraping, cumulative scraping, indegree, outdegree and betweenness of the people who scraped the most popular item among 100 items.

• Annals of Clinical Neurophysiology
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• v.25 no.2
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• pp.93-102
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• 2023

Background: We aimed to identify any differences in the structural covariance network based on structural volume and those in the functional network based on cerebral blood flow between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura. Methods: We prospectively enrolled 27 patients with migraine without aura, all of whom had unilateral migraine pain. We defined the ipsilateral hemisphere as the side of migraine pain. We measured structural volumes on three-dimensional T1-weighted images and cerebral blood flow using arterial spin labeling magnetic resonance imaging. We then analyzed the structural covariance network based on structural volume and the functional network based on cerebral blood flow using graph theory. Results: There were no significant differences in structural volume or cerebral blood flow between the ipsilateral and contralateral hemispheres. However, there were significant differences between the hemispheres in the structural covariance network and the functional network. In the structural covariance network, the betweenness centrality of the thalamus was lower in the ipsilateral hemisphere than in the contralateral hemisphere. In the functional network, the betweenness centrality of the anterior cingulate and paracingulate gyrus was lower in the ipsilateral hemisphere than in the contralateral hemisphere, while that of the opercular part of the inferior frontal gyrus was higher in the former hemisphere. Conclusions: The present findings indicate that there are significant differences in the structural covariance network and the functional network between the ipsilateral and contralateral hemispheres of pain in patients with episodic migraine without aura.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.21-43
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• 2008

The task network which is formed of different individuals can be recognized as a social network. Therefore, the way to communicate with people inside or outside the network has considerable influence on their outcome. Moreover, the position on which a member stands in a network shows the different effects of the information systems supporting communication with others. In this paper, it is to be studied how personal CMC (computer-mediated communication) tools affect the mission that those who work for a network perform through diverse task networks. Especially, we focused on synchronicity of CMC. On this score, the perspective of Media Synchronicity Theory was taken that had been suggested by criticizing Media Richness Theory. It is the objective, from this perspective, to find which characteristics of networks make the value of IT supporting synchronicity high. In the research trends of social networks, there have been two traditional perspectives to explain the effect of network: embeddedness and diversity ones. These differ from the aspect which type of social network can provide much more economic benefits. As similar studies have been reported by various researchers, these are also divided into the bonding and bridging views which are based on internal and external tie, respectively, Size, density, and centrality were measured as the characteristics of personal task networks. Size means the level of relationship between members. It is the total number of other colleagues who work with a specific member for a certain project. It means, the larger the size of task network, the more the number of coworkers who interact each other through the job. Density is the ratio of the number of relationships arranged actually to the total number of available ones. In an ego-centered network, it is defined as the ratio of the number of relationship made really to the total number of possible ones between members who are actually involved each other. The higher the level of density, the larger the number of projects on which the members collaborate. Centrality means that his/her position is on the exact center of whole network. There are several methods to measure it. In this research, betweenness centrality was adopted among them. It is measured by the position on which one member stands between others in a network. The determinant to raise its level is the shortest geodesic that represents the shortest distance between members. Centrality also indicates the level of role as a broker among others. To verify the hypotheses, we interviewed and surveyed a group of employees of a nationwide financial organization in which a groupware system is used. They were questioned about two CMC applications: MSN with a higher level of synchronicity and email with a lower one. As a result, the larger the size of his/her own task network, the smaller its density and the higher the level of his/her centrality, the higher the level of the effect using the task network with CMC tools. Above all, this positive effect is verified to be much more produced while using CMC applications with higher-level synchronicity. Among the a variety of situations under which the use of CMC gives more benefits, this research is considered as one of rare cases regarding the characteristics of task network as moderators by focusing ITs for the operation of his/her own task network. It is another contribution of this research to prove empirically that the values of information system depend on the social, or comparative, characteristic of time. Though the same amount of time is shared, the social characteristics of users change its value. In addition, it is significant to examine empirically that the ITs with higher-level synchronicity have the positive effect on productivity. Many businesses are worried about the negative effect of synchronous ITs, for their employees are likely to use them for personal social activities. However. this research can help to dismiss the concern against CMC tools.

• Journal of dental hygiene science
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• v.18 no.6
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• pp.380-388
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• 2018

This research team extracted keywords from 953 papers published in the Journal of Dental Hygiene Science from 2001 to 2018 for keyword and centrality analyses using the Keyword Network Analysis method. Data were analyzed using Excel 2016 and NetMiner Version 4.4.1. By conducting a deeper analysis between keywords by overall keyword and time frame, we arrived at the following conclusions. For the 17 years considered for this study, the most frequently used words in a dental science paper were "Health," "Oral," "Hygiene," and "Hygienist." The words that form the center by connecting major words in the Journal of Dental Hygiene through the upper-degree centrality words were "Health," "Dental," "Oral," "Hygiene," and "Hygienist." The upper betweenness centrality words were "Dental," "Health," "Oral," "Hygiene," and "Student." Analysis results of the degree centrality words per period revealed "Health" (0.227), "Dental" (0.136), and "Hygiene" (0.136) for period 1; "Health" (0.242), "Dental" (0.177), and "Hygiene" (0.113) for period 2; "Health" (0.200), "Dental" (0.176), and "Oral" (0.082) for period 3; and "Dental" (0.235), "Health" (0.206), and "Oral" (0.147) for period 4. Analysis results of the betweenness centrality words per period revealed "Oral" (0.281) and "Health" (0.199) for period 1; "Dental" (0.205) and "Health" (0.169) for period 2, with the weight then dispersing to "Hygiene" (0.112), "Hygienist" (0.054), and "Oral" (0.053); "Health" (0.258) and "Dental" (0.246) for period 3; and "Oral" (0.364), "Health" (0.353), and "Dental" (0.333) for period 4. Based on the above results, we hope that further studies will be conducted in the future with diverse study subjects.

• Journal of the Korean association of regional geographers
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• v.16 no.4
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• pp.369-386
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• 2010

Migration usually derived from the gap of spatial efficiency and the attractiveness difference between the origin and the destination puts forth significant impact on the regional dynamics of population. Both migration and regional planning or policy are structurally interconnected, exerting impact each other within the circular loops. In order to observe migration characters in the regional dimension, this research depends on social network analysis(SNA) methods which easily portray interrelationship and its weight between the origin and the destination. In specific, it focuses on the application of centrality indicators in order to understand the in- and out-migration patterns and visualize them with spring graphs, pinpointing the in- and out-migration administrative units. This research deals with three migration patterns in 2001 and 2008, respectively: i) in- and out-migration between the nation and Chungbuk Province; ii) in- and out-migration within Chungcheong Areas; and iii) in- and out-migration within Chungbuk Province. Judging from Chungbuk examples, the highest in-migration was recorded at Heungduck District in terms of in- and out-migration between the nation and Chungbuk Province. Seoul and Gyeonggi were two major origins towards Chungbuk Province. Within Chungcheong Areas, Daejeon produced the highest in-migration in 2001. However, Chungnam took that position in 2008.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.482-487
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• 2015

This paper presents the results and the process of extracting correlations between events of prescriptions and examinations using graph-modeling and node centrality measures on a medical dataset of 11,938 patients with diabetes mellitus. As the data is stored in relational form, RDB2Graph framework was used to construct effective graph models from the data. Personalized PageRank was applied to analyze correlation between prescriptions and examinations of the patients. Two graph models were constructed: one that models medical events by each patient and another that considers the time gap between medical events. The results of the correlation analysis confirm current medical knowledge. The paper demonstrates some of the note-worthy findings to show the effectiveness of the method used in the current analysis.

• The Research Journal of the Costume Culture
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• v.28 no.6
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• pp.755-770
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• 2020

As the postsecondary school-age population continues to decline, universities are building identities to differentiate themselves and create a favorable impression among this cohort. We investigated the role of logo-bearing products as a way of promoting university identity, specifically, the effects of ingroup ties, ingroup affect, and centrality on attitude toward university logo products and purchase intention. This study further examined the moderating effects of perceived university prestige on the relationship between logo product attitude and in-store purchase intention, and the moderating effect of online shopping frequency on the relationship between logo product attitude and online purchase intention. We conducted a survey of undergraduate and graduate students at a university in Seoul. Survey responses (N=561) were collected and processed using SPSS 23.0. Multiple regression analysis showed that ingroup ties and affect had significant effects on product attitude. However, centrality had no significant effect on attitude toward the product. Product attitude had a direct significant effect on both in-store and online purchase intention. Perceived university prestige moderated the relationship between product attitude and in-store purchase intention. Moreover, online shopping frequency moderated the relationship between product attitude and online purchase intention. The results of this study are expected to provide fundamental knowledge for developing product strategy of logo products.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.117-122
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• 2021

In order to reveal the co-research relationship with key research institutes in the computer field in Korea, which have high competitiveness in the ICT field, this paper analyzes the co-author network of research institutes based on the papers of Korean journals. For this study, 15 computer journals published in Korea were selected and collected for the past 5 years. In addition, authors, affiliated institutions, and country information were extracted from the papers, and experimental data were produced using institutional identification data and SNA analysis techniques. Through this, statistical analysis was performed on researchers, research institutes, and countries, and the centrality of research institutes was measured through co-authored network analysis and visualized as a map. The results of the research that analyzed the co-author relationship based on the papers in computer science journals published in Korea are as follows. First, the status of co-author relations among researchers was statistically analyzed in detail. The number of authors, the number of co-authors, and statistics by co-authoring countries, as well as the ratio of co-authored research by institution and the ratio of co-authored by country were revealed. The co-authoring status of papers in English journals was analyzed separately to compare and analyze characteristics. Second, the centrality of each individual was measured through the co-authored network analysis of the identified researchers, institutions and countries affiliated with the institution, and the frequency of connection between data by level was identified. In addition, the co-authorization network between research institutes was visualized and presented as a map so that the overall view of the co-authoring network was presented, and the connection frequency between the institutes was checked. It is possible to recommend a research partner based on the co-authoring behavior of Korean computer researchers and the co-authoring relationship between major research institutes. For this, additional research is needed to analyze the subject areas of each institution.