• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.955-964
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• 2014

The more importance of international collaboration has increased, the more studies on statues of international collaboration are increasing. However, few studies have attempted to identify the international collaboration. This article aims at a multidirectional characterization of the international collaboration in the field of Computer Science by analysis of articles published in the SCOPUS database. We applied Probabilistic Affinity Index(PAI) and Indicator of Collaboration Strength(ICS) for measuring the intensity of scientific collaboration among countries, and index of Incremental Citation Impact(ICI) for measuring the quality of international collaboration. These analyses identify the trends of international collaboration in the field of Computer Science and it's effect by nation.

• Journal of the Korean Society for information Management
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• v.28 no.2
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• pp.97-115
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• 2011

A large and reliable citation database is necessary to identify and analyze citation behavior of Korean researchers in science and technology. Korea Institute of Science and Technology Information (KISTI) built the Korea Science Citation Database (KSCD), and have provided Korea Science Citation Index (KSCI) and Korea Journal Citation Reports (KJCR) services. In this article, citing behavior of Korean scientists on Korean journals was examined by using the KSCD that covers 459 Korean core journals. This research dealt with (1) statistical numeric information of journals in KSCD, (2) analysis of document types cited, (3) ratio of domestic to international documents cited and ratio of citing different disciplines, (4) analysis on immediacy index, peak time, and half-life of cited documents, and (5) analysis on impact of journals based on KJCR citation indicators. From this research, we could find the immediacy citation rate (average 2.36%), peak-time (average 1.7 years) and half-life (average 5.2 years) of cited journals in Korea. We also found that the average journal self-citation rate is more than 50% in every field. In sum, citing behavior of Korean scientists on Korean journals was comprehensively identified from this research.

• Journal of the Korean Society for information Management
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• v.30 no.4
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• pp.7-29
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• 2013

As interdisciplinary research has been dominant in various fields, the purpose of this study is to analyze the relationship between interdisciplinarity and research impact in the field of Library and Information Science. For a data set, ten journals ranked as the top of 2011 JCR's in terms of JIF (Journal Impact Factor) were selected. The citation data of 1,873 articles from the ten journals were collected from the WoS during the period from 2006 to 2010. In order to achieve the purpose of this study, as network analysis was conducted to investigate the interdisciplinarity of LIS field, interdisciplinarity indicators, and research impact factors were statistically analyzed. The findings of this study confirmed the interdisciplinary knowledge structure of the LIS field as previous studies identified. More importantly, this study demonstrated that a positive correlation existed between interdisciplinarity represented as betweenness centrality and research impact.

• The Research Journal of the Costume Culture
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• v.27 no.4
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• pp.299-309
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• 2019

Citation frequency is an important factor in evaluating journal quality and is used as a measure of journal impact. The citation index of a paper plays an important role in linking papers with groups of other academic papers, forming a huge and complex network. This study examines the intellectual structure of apparel research through the bibliometric citation analysis of The Research Journal of the Costume Culture (RJCC). In order to analyze the changes in the intellectual structure of the RJCC, we used the Korea Citation Index's (KCI) data (highly citing journals and highly cited journals). The NodeXL, a social network analysis tool, was used to examine the connection structure between journals. In order to identify the academic influence of the RJCC, we used the KCI journal citation index. Our findings indicate that the RJCC has a high centrality index among the clothing-oriented journals in the same life sciences field. A look at the journals citing the RJCC and the journals cited within the RJCC also showed that more journals of diverse fields have been recently linked through their citations. This suggests that a convergence of interdisciplinary research is underway in the field of clothing. As a result of examining international journals cited in the RJCC, it was confirmed that they were cited in prominent international journals in various fields.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.99-109
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• 2016

During the last two decades, impact factor has been widely used as a journal evaluation metric that differentiates the influence of a specific journal compared with other journals. However, impact factor does not provide a reliable metric between journals in different subject categories. For example, higher impact factors are given to biology and general sciences than those assigned to other traditional engineering and social sciences. This study initially analyzes the trend of the time series of the impact factors of the journals listed in Journal Citation Reports during the last decade. This study then proposes new journal evaluation metrics that adjust the impact factors across different subject categories. The proposed metrics possibly provides a consistent measure to mitigate the differences in impact factors among subject categories. On the basis of experimental results, we recommend the most reliable and appropriate metric to evaluate journals that are less dependent on the characteristics of subject categories.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.341-354
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• 2011

Analyzing the relationships among the parameters for quantifying the quality of research published in journals is a challenging task. In this paper, we analyze the relationships between the impact factor, h-index, and g-index of a journal. To keep our analysis simple and easy to understand, we consider a generalized version of the impact factor where there is no time window. In the absence of the time window, the impact factor converges to the number of citations received per paper. This is not only justified for the impact factor, it also simplifies the analysis of the h-index and g-index as well because addition of a time window in the form of years complicates the computation of indices too. We derive the expressions for the relationships among impact factor, h index, and g-index and validate them using a given set of publication-citation data.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2004.11a
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• pp.273-285
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• 2004

• Journal of Korean Neurosurgical Society
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• v.64 no.5
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• pp.675-676
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• 2021

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.377-394
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• 2009

There are some limitations in the existing bibliometric methods to satisfy the various requests of the interest parties including researchers, managers, policy makers to identify 1) which research group or researcher is the key player, and the overall trends of the particular technological sub-fields, 2) which research groups, institutions or countries mainly use their research outputs, 3) what are the spin-offs from research outputs to some scientific and technological fields, 4) in which levels they are when comparing their quantitative and qualitative research outputs to those of other competitive institutions. It is essential to develop new informetric indicators and methodologies in order to satisfy stakeholder's various demands and to strengthen qualitative analysis in measuring research performance. This study suggested informetric indicators such as article quality index, citation impact index, international cooperation index, excellent article production index and methodologies including citation analysis, text mining.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.