• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.133-154
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• 2016

Interdisciplinary approach has been recognized as one of key strategies to address various and complex research problems in modern science. The purpose of this study is to investigate the interdisciplinary characteristics and structure of the field of big data. Among the 1,083 journals related to the field of big data, multiple Subject Categories (SC) from the Web of Science were assigned to 420 journals (38.8%) and 239 journals (22.1%) were assigned with the SCs from different fields. These results show that the field of big data indicates the characteristics of interdisciplinarity. In addition, through bibliographic coupling network analysis of top 56 journals, 10 clusters in the network were recognized. Among the 10 clusters, 7 clusters were from computer science field focusing on technical aspects such as storing, processing and analyzing the data. The results of cluster analysis also identified multiple research works of analyzing and utilizing big data in various fields such as science & technology, engineering, communication, law, geography, bio-engineering and etc. Finally, with measuring three types of centrality (betweenness centrality, nearest centrality, triangle betweenness centrality) of journals, computer science journals appeared to have strong impact and subjective relations to other fields in the network.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.115-124
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• 2022

The purpose of this study is to analyze and present keywords, trends, and language networks of keywords for each year of the pedagogical exam of the secondary teacher's employment exam for the 2019~2022 school year. The main research methods were text mining technique and language network analysis method, and analysis programs were KrKwic, Wordcloud Maker, Ucinet6, NetDraw, etc. The research results are as follows; First, keywords such as teacher, student, curriculum, class, and evaluation appeared in the top rankings, and keywords (online, wiki, discussion ceremony, information, etc.) that reflect the recent online class progress in the current COVID-19 situation also tended to appear. The keywords with high frequency of occurrence in the four-year integrated text were student(44), teacher(39), class(27), school(18), curriculum(16), online(10), and discussion method(8). Second, the overall language network of the keywords with high frequency of 4 years showed a significant level of density(0.566), total number of links(492), and average degree of links(16.4). The degree centrality was found in the order of teacher(199.0), class(197.0), student(185.0), and school(150.0). Betweenness centrality was found in the order of teacher(30.859), class(18.956), student(16.054), and school (15.745). It is expected that the results of this study will serve as data to be considered for preparatory teachers, institutions and related persons, and teachers and administrators of secondary school teacher training institutions.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.59-76
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• 2023

This study examines critical issues and topics related to services using YouTube videos and research publications. We analyzed 2,853 YouTube videos and 19,973 research papers related to services, released during the 2013-June, 2023 period, using text mining and network analysis. In addition, the collected data was divided into pre- and post-COVID-19 pandemic periods to explore how key issues and topics regarding services have changed. These papers were sequentially analyzed through text mining and network construction and procedures. The results indicate that the central themes of YouTube videos were IT, data, and solution, while academic research focused on service quality, quality, and customer satisfaction. Regarding ego network analysis, the key issues in YouTube video contents revolved primarily around words related to the service industry. Although it was found that they generally lacked specific industry fields, academic papers explored diverse issues in various service fields. The results of this study can be utilized to understand changes in customer concerns in the service industry from practical and academic perspectives.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.107-115
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• 2013

Various networks can be observed in the world. Knowledge networks which are closely related with technology and research are especially important because these networks help us understand how knowledge is produced. Therefore, many studies regarding knowledge networks have been conducted. The assortativity coefficient represents the tendency of connections between nodes having a similar property as figures. The relevant characteristics of the assortativity coefficient help us understand how corresponding technologies have evolved in the keyword-based patent network which is considered to be a knowledge network. The relationships of keywords in a knowledge network where a node is depicted as a keyword show the structure of the technology development process. In this paper, we suggest two hypotheses basedon the previous research indicating that there exist core nodes in the keyword network and we conduct assortativity analysis to verify the hypotheses. First, the patents network based on the keyword represents disassortativity over time. Through our assortativity analysis, it is confirmed that the knowledge network shows disassortativity as the network evolves. Second, as the keyword-based patents network becomes disassortavie, clustering coefficients become lower. As the result of this hypothesis, weconfirm the clustering coefficient also becomes lower as the assortative coefficient of the network gets lower. Another interesting result concerning the second hypothesis is that, when the knowledge network is disassorativie, the tendency of decreasing of the clustering coefficient is much higher than when the network is assortative.

• Journal of Korea Technology Innovation Society
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• v.21 no.1
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• pp.33-63
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• 2018

The purpose of this study is to identify trends and to analyze knowledge structure and knowledge flow of studies on science and technology policy adopting the keyword network analysis. For analysis, we established a data set of published papers in the Journal of Korea Technology Innovation Society and Journal of Technology Innovation from 1993 to 2016. As a result of analysis, a great part of existing researches have been carried out in Seoul and Daejeon area, universities and public research institute. So it should be carried out in diversified form rather than being concentrated on specific regions or research performing subjects in the future. By research scope, more than 70% of research were carried out in 'R&D management' and 'technology innovation'. In the future, more research must be carried out in 'public process of science and technology' and 'public management of science and technology'. On the other hand, we performed the keyword network analysis to identify the knowledge structure of studies on science and technology policy. As a result of analysis, it was clustered into 'public process of science and technology', 'public management of science and technology', 'R&D management' and 'technology innovation', So It has not been different from research scope proposed by Yi, Kim and Oh(2016). And also, in earlier stage, research topics were general such as researchers and R&D investment. But as time goes by, topics were more diversified and subdivided. Therefore, in future, the research scope of studies on science and technology policy should be further expanded in terms of 'public process of science and technology', 'public management of science and technology', 'R&D management' and 'technology innovation', and systematic knowledge structure should be formed.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.85-105
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• 2012

In recent years, IT advancement has brought out the new Internet communication environment such as online social network services, where people are connected in global network without temporal and spatial limitation. The popular use of online social network helps people share their experience and preference for specific products and services, thus holding large potential to significantly affect firms' business performance through Word-of-Mouth (WOM). This study examines the role of online social network in raising WOM effect on the movie industry by comparing with the similar role of Internet portal, another major online communication channel. Analyzing 109 movies and data from both Twitter and Naver movie, we found that significant WOM effect exists simultaneously in both Twitter and Naver movie. However, we also found that different figures of online viral effects exist depending on the popularity of movies. In the hit movie group, before the movie release, the WOM effect occurs only in Twitter while the WOM effect arises in both Twitter and Naver movie at the same time after the movie release. In the less-popular (or niche) movie group, the WOM effect occurs in both Twitter and Naver movie only before the movie release. Our findings not only deepen theoretical insights into different roles of the two online communication channels in provoking the WOM effect on entertainment products but also provide practitioners with incentive to utilize SNS as strategic marketing platform to enhance their brand reputations.

• Knowledge Management Research
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• v.22 no.1
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• pp.217-242
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• 2021

The purpose of this study is to examine the research trends in the filed of individual knowledge hiding through keyword network analysis. As individuals intentionally hide their knowledge beyond not sharing their knowledge in organizations and the research on knowledge hiding steadily spreads, it is necessary to examine the research trends regarding knowledge hiding behaviors. For keyword network analyses, we collected 346 kinds of 578 keywords from 120 articles associated with knowledge hiding behaviors. We also transformed the keywords to 86 nodes and 667 links by data standardizing criteria and finally analyzed the keyword network among them. Moreover, this study scrutinized knowledge hiding trends by comparing the conceptual model for knowledge hiding based on literature review and the network structure based on keyword network analysis. As results, first, the network centrality degree, knowledge sharing, creativity, and performance was higher than others in Degree, Betweenness, Closeness centrality. Second, this study analyzed ego networks about psychological ownership and individual emotion theoretically associated with knowledge hiding and explored the relationship between variables through comparing with the conceptual model for knowledge hiding. Finally, the study suggested theoretical and practical implications and provided the limitations and suggestions for future research based on study findings.

• Journal of Information Technology and Architecture
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• v.11 no.4
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• pp.471-483
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• 2014

The purpose of this study was to look over the sharing and flow of information on tourism tourist destination made through social media by utilizing social network analysis. In this research for compared the exchange and diffusion relationships and made information sharing among users of the network group for the Seoul / Busan Tourism Twitter. The first part of analysis dealt with the network centralization and information dissemination patterns from a global perspective. The second part was an analysis of nodes with the highest degree centrality in order to identify the most influential user within the Twitter network and determine the information flow and user characteristics with respect to the information dissemination pattern in Seoul/Busan tourism Twitter. The results scientific evidence was presented that social media users' information search behavior information to understand the sharing and spreading patterns, social media as a marketing tool, simple products and services that will ultimately provide the desired information detainee information is not a means of promoting utilization was presented.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.157-182
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• 2018

As data management and processing techniques have been developed rapidly in the era of big data, nowadays a lot of business companies and researchers have been interested in long tail data which were ignored in the past. This study proposes methods for generating and controlling a network of technical terms based on text mining technique to enhance data utilization in the distribution of long tail theory. Especially, an edit distance technique of text mining has given us efficient methods to automatically create an interlinking network of technical terms in the scholarly field. We have also used linked open data system to gather experimental data to improve data utilization and proposed effective methods to use data of LOD systems and algorithm to recognize patterns of terms. Finally, the performance evaluation test of the network of technical terms has shown that the proposed methods were useful to enhance the rate of data utilization.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.3
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• pp.383-402
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• 2016

The purpose of this study is to study library marketing research trends in Korea and other countries through the analysis of author keyword network of peer-reviewed journal articles. The author keyword was collected from four major LIS journals in Korea and Scopus academic database for other countries'. The data was analyzed using NetMiner4 software. The results of the study were as follows: 1) In Korea, lots of library marketing studies focused on public libraries. However, there was a range of library marketing researches focused on academic libraries in other countries, 2) In Korea, there was not a variety of subjects of library marketing studies and the studies were mainly led by a few scholars, 3) In other countries, many scholars paid attention to digital library marketing through social media and/or web, and 4) there little library marketing studies focused on school libraries both in Korea and other countries.