• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.6
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• pp.834-844
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• 2014

This study investigated original articles published in the Journal of the Korean Society of Clothing and Textiles (JKSCT) from 1977 through 2013 with a consideration of the research collaboration structure. Two international journals were chosen: Textile Research Journal (TRJ) and International Journal of Clothing Science and Technology (IJCT) in order to compare the clothing science research trends of JKSCT-publications to international trends. The collected data from the three journals were used to probe periodic changes in the number of publications and nationality of authors to find the relative international position of Korean clothing and textile researchers. Figures, tables, and references in each article were counted to suggest the most suitable way to express and interpret clothing science results. In addition to the quantified data analysis, a qualified analysis was investigated with the co-author network analysis. The findings revealed an increase in the number of published articles in JKSCT until 2009 with the rapid decrease after. The number of co-authors in JKSCT was relatively small compared to TRJ and IJCT but growing in the clothing and textile science group. The number of references in JKSCT increased 3 times from 1977 to 2013; therefore, it was assumed there is more recent active clothing and textile research. Lastly, a pattern of authors' interaction and the most contributed authors in the network was illustrated in the clothing and textile science group. The present study confirms that JKSCT has made significant progress toward knowledge development in the clothing and textile field and suggests that the analysis of accumulative knowledge helps researchers broaden the scale and approach of studies.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.89-115
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• 2019

This study was conducted to present the stylistic differences between Arthur Conan Doyle and Agatha Christie, famous as writers of classical mystery novels, through data analysis, and further to present the analytical methodology of the study of style based on text mining. The reason why we chose mystery novels for our research is because the unique devices that exist in classical mystery novels have strong stylistic characteristics, and furthermore, by choosing Arthur Conan Doyle and Agatha Christie, who are also famous to the general reader, as subjects of analysis, so that people who are unfamiliar with the research can be familiar with them. The primary objective of this study is to identify how the differences exist within the text and to interpret the effects of these differences on the reader. Accordingly, in addition to events and characters, which are key elements of mystery novels, the writer's grammatical style of writing was defined in style and attempted to analyze it. Two series and four books were selected by each writer, and the text was divided into sentences to secure data. After measuring and granting the emotional score according to each sentence, the emotions of the page progress were visualized as a graph, and the trend of the event progress in the novel was identified under eight themes by applying Topic modeling according to the page. By organizing co-occurrence matrices and performing network analysis, we were able to visually see changes in relationships between people as events progressed. In addition, the entire sentence was divided into a grammatical system based on a total of six types of writing style to identify differences between writers and between works. This enabled us to identify not only the general grammatical writing style of the author, but also the inherent stylistic characteristics in their unconsciousness, and to interpret the effects of these characteristics on the reader. This series of research processes can help to understand the context of the entire text based on a defined understanding of the style, and furthermore, by integrating previously individually conducted stylistic studies. This prior understanding can also contribute to discovering and clarifying the existence of text in unstructured data, including online text. This could help enable more accurate recognition of emotions and delivery of commands on an interactive artificial intelligence platform that currently converts voice into natural language. In the face of increasing attempts to analyze online texts, including New Media, in many ways and discover social phenomena and managerial values, it is expected to contribute to more meaningful online text analysis and semantic interpretation through the links to these studies. However, the fact that the analysis data used in this study are two or four books by author can be considered as a limitation in that the data analysis was not attempted in sufficient quantities. The application of the writing characteristics applied to the Korean text even though it was an English text also could be limitation. The more diverse stylistic characteristics were limited to six, and the less likely interpretation was also considered as a limitation. In addition, it is also regrettable that the research was conducted by analyzing classical mystery novels rather than text that is commonly used today, and that various classical mystery novel writers were not compared. Subsequent research will attempt to increase the diversity of interpretations by taking into account a wider variety of grammatical systems and stylistic structures and will also be applied to the current frequently used online text analysis to assess the potential for interpretation. It is expected that this will enable the interpretation and definition of the specific structure of the style and that various usability can be considered.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.279-300
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• 2019

This study aims to analyze and to demonstrate the research trends and intellectual structure in the field of catalog in the 2000s and 2010s through co-word analysis. The field of catalog had firmly established its own research area and Many differences were found in research trends and intellectual structures in the 2000s and 2010s. First, the average number of articles decreased by 4.2 in the 2010s compared to the 2000s, but the number of author keywords was not significantly different. Only 22.2% of keywords appeared more than three times in both periods, and 77.8% of keywords appeared more than three times in one period. Second, in terms of intellectual structure, the 2000s, represented by three-level clusters, formed a more complex network than the 2010s, represented by two-level clusters. Third, as a result of examining the changes in the characteristics of each cluster, there were some research topics with few changes, but many research topics were more actively progressed or subdivided, and decreased. The results of this study are meaningful in that they can visually grasp the intellectual structure along with the trend of the age of catalogue, and can prepare for related education and research by predicting the future.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.141-157
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• 2021

In this study, we aimed to understand research trends of domestic artificial intelligence research. To achieve the goal, we applied network analysis and dynamic topic modeling to domestic research papers on artificial intelligence. Among the papers that have been indexed in KCI (Korean Journal of Citation Index) by 2020, metadata and abstracts of 2,552 papers where the titles or indexed keywords include 'artificial intelligence' both in Korean and English were collected. Keyword, affiliation, subject field, and abstract were extracted and preprocessed for further analyses. We identified main keywords in the field by analyzing keyword co-occurrence networks as well as the degree and characteristics of research collaboration between domestic and foreign institutions and between industry and university by analyzing institutional collaboration networks. Dynamic topic modeling was performed on 1845 abstracts written in Korean, and 13 topics were obtained from the labeling process. This study broadens the understanding of domestic artificial intelligence research by identifying research trends through dynamic topic modeling from abstracts as well as the degree and characteristics of research collaboration through institutional collaboration networks from author affiliation information. In addition, the results of this study can be used by governmental institutions for making policies in accordance with artificial intelligence era.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.36 no.2
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• pp.60-75
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• 2023

Objectives : A bibliometric approach using network analysis was applied to explore the global trends of research on herbal medicine for atopic treatment. Methods : Articles related to herbal medicine on atopic treatment from 2003 to 2022 were retrieved from Web of Science Core Collection. Extracted records were analyzed according to the publication year, research area, journal title, country, organization, author and keyword. The VOSviewer program was used to visualize the trends and the research hotspots in herbal medicine for atopy. Results : Analysis of 406 articles indicated the consistent increase of using herbal medicine for atopic treatment over the last 20 years. The most productive country and research organization in issuing articles were South Korea and Kyunghee university. Many articles have been published in research areas such as 'integrative complementary medicine' and 'pharmacology pharmacy'. By evaluating the total link strength, the average publication year and the average citations of countries and authors, the influential countries and authors were identified. A network analysis based on the co-occurrence and the publication year of keywords revealed the relevant characteristics and trends of herbal medicine for atopy. The most up-to-date keywords were 'topical application', 'skin barrier' and 'care'. Conclusions : This bibliometric study examined the overall trends and the time-based development of herbal medicine for atopic treatment. The current study would be useful not only for grasping the global network hub of research on herbal medicine for atopic treatment, but also to explore the new directions for future research.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.563-572
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• 2024

Image processing and computer vision technologies are becoming increasingly important in a variety of application fields that require techniques and tools for sophisticated image analysis. In particular, image segmentation is a technology that plays an important role in image analysis. In this study, in order to identify recent research trends on image segmentation techniques, we used the Web of Science(WoS) database to analyze the R&D topography based on the network structure of the author's keyword co-occurrence matrix. As a result, from 2015 to 2023, as a result of the analysis of the R&D map of research articles on image segmentation, R&D in this field is largely focused on four areas of research and development: (1) researches on collecting and preprocessing image data to build higher-performance image segmentation models, (2) the researches on image segmentation using statistics-based models or machine learning algorithms, (3) the researches on image segmentation for medical image analysis, and (4) deep learning-based image segmentation-related R&D. The scientometrics-based analysis performed in this study can not only map the trajectory of R&D related to image segmentation, but can also serve as a marker for future exploration in this dynamic field.

• Journal of the Korean Society for information Management
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• v.41 no.2
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• pp.1-18
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• 2024

This study aims to compare ego-centered journal citation identities among four domestic journals in library and information science. Ego-centered citation identity refers to the set of authors that an author frequently cites. The target journals for this study are Journal of the Korean Society for Library and Information Science (KSLIS), Journal of the Korean Biblia Society for Library and Information Science (KBIBLIA), Journal of Korean Library and Information Science Society (KLISS), and Journal of the Korean Society for Information Management (KOSIM). As a result of citation/citee ratio (CCR), self-citing rates (SCR), and journal co-cited analysis, the journal citation identities of four journals contained the other three journals besides the ego journal and JASIST. Furthermore, KOSIM had the most diverse range of journal citation identity and the four journals mattered the intra-journal information. KLISS showed the most unique cited journal network structure among the four journals.

• Convergence Security Journal
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• v.17 no.1
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• pp.15-30
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• 2017

Since the 1990s, fingerprint recognition has attracted much attention among scholars. There have been numerous studies on fingerprint recognition. However, most of the academic papers have focused mainly on how to make a technical advance of fingerprint recognition. there has been no significant output in the analysis of the research trends in fingerprint recognition. It's essential part to describe the overall structure of fingerprint recognition to make further studies much more efficient and effective. To this end, the primary purpose of this article is to deliver an overview of the research trends on fingerprint recognition based on network analysis. This study analyzed abstracts of the 122 academic journals ranging from 1990 to 2015. For gathering those data, the author took advantage of an academic searchable data base-RISS. After collecting abstracts, cleaning process was carried out and key words were selected by using Krwords and R; co-occurrence symmetric matrix made up of key words was created by Ktitle; and Netminer was employed to analyze closeness centrality. The result achieved from this work included followings: research trends in fingerprint recognition from 1990 to 2000, 2001 to 2005, 2006 to 2010, and 2011 to 2015.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.429-450
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• 2023

The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.