• Journal of Information Science Theory and Practice
• /
• v.7 no.2
• /
• pp.23-31
• /
• 2019

We report results of selection-bias-free approaches to the analysis of the impact of open access (OA) models on citation metrics. We studied reference groups of Gold and Green OA articles and the group of non-OA (Paywall) articles with the new functionality of the Web of Science Core Collection database, the InCites platform of Clarivate Analytics, and the Dimensions database of Digital Science. For each reference group we obtained the values of the percent of cited articles and citation impact and their dependence on the depth of the citation period. Different research fields were analyzed in two schemas of the InCites platform. We report the higher values and growth rates of the citation metrics: citation impact and %Cited, in the OA reference groups over the Paywall group. The Green OA articles demonstrate the highest values of citation metrics among all the OA models. Dependence of the value of citation impact on citation period follows linear law with R2 values close to 0.9-1.0. The overall annual growth rates of citation impact of the Green OA, Gold OA, and the Paywall articles, k equal, respectively, 3.6, 2.4, and 1.4 in Dimensions and 4.6, 3.6, and 2.3 in the Web of Science Core Collection. We suppose that earlier results reported for the articles in pure OA journals vs. articles in Paywall journals were affected by the high citation impact of the Green and Hybrid OA articles that could not be elucidated in the Paywall journals at that time.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.259-264
• /
• 2001

This paper presents impact factors of domestic journals in mechanical engineering area to present an objective data for journal evaluation. For this purpose, reference data of 47 Korean journals are databased and analyzed. From the developed database, impact factor, immediacy index and self citation index are calculated.

• Journal of Information Management
• /
• v.43 no.3
• /
• pp.23-41
• /
• 2012

Citation analysis studies have reported many problems associated with data coverage problems common to popular citation databases such as Web of Science(WoS). In addition, the studies that analyzed citation patterns of Korean publications found that up to 75% of references in Korean publications were to international publications. As a first step in investigating the international coverage of WoS database, the study investigated the effect of adding citation data from Korea Science Citation Database(KSCD) to the impact factors and journal rankings of the journals listed in Journal Citation Reports. Specifically, the study mined the reference data from top 5 Korean Library and Information Science(KLIS) journals to recompute the impact factors reported in JCR 2009. Since the resulting journal rankings did not significantly differ from JCR 2009 rankings except for minor ranking changes, we analyzed additional citation data from 45 computer science and electrical engineering journals. Although the overall ranking difference was not statistically significant, one of the ranking partitions showed significant change. Such study findings despite its limited data sample suggest the potential impact of non-Western citation databases such as KSCD to bibliometric indicators provided by popular citation databases like WoS.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.7 no.6
• /
• pp.1353-1362
• /
• 2012

Many studies have demonstrated that articles from international collaborations are more cited than articles from domestic collaborations. However, difference between the citation impact of international and domestic co-authored papers is supposed to be widened due to the collaboration strategy adopted by individual institute. In short, each institute will show the significantly different citation impact between international and domestic co-authored papers. In this paper, we applied the index of Incremental Ciation Impact(ICI) to identify the different value of citation impact between international and domestic co-authored papers for research institutes of KRCF, results of which will be understood under the strategy of international research collaboration.

• Journal of Information Processing Systems
• /
• v.14 no.4
• /
• pp.916-925
• /
• 2018

The academic research performance is often quantitatively measured by means of using citation frequency. The citation frequency-based indicators, such as h-index and impact factor, are commonly used reflecting the citation quality to some extent. However, these frequency-based indicators are usually carried out based on the assumption that all citations are equal. This may lead to biased evaluations in that, the attributes of the citing objects and cited objects are significant. A high-accuracy evaluation method is needed. In this paper, we review various citation quality-based evaluation indicators, and categorize them considering the algorithms being applied. We discuss the pros and cons of these indicators, and compare them from four dimensions. The outcomes will be useful for our further research on distinguishing citation quality.

• Journal of the Korean Society for Library and Information Science
• /
• v.52 no.4
• /
• pp.71-90
• /
• 2018

The importance of citation measures has been increasing in the evaluation of scholarly journals and it becomes a major issue for Korean Citation Index (KCI) journals. The Journal Impact Factor (JIF), a widely used measure for academic journals, has a problematic issue that it does not include the number of citations for a paper immediately made in the year in which the cited paper was published. On the contrary, the Diachronous Impact Factor (IMP) includes the number of citations made in the published year, but IMP is a measure for papers published a few years ago, not in the last year. It does not represent the recent value of journals effectively. To overcome these problems, Total Impact Factor (TIF) and Mean Impact Factor (MIF) are proposed as new journal citation indicators. This study calculated the performance of proposed indicators experimentally on KCI data. The result shows that TIF is a promising measure for the multidimensional evaluation of humanities and social sciences journals in Korea because it has high stability by year and includes the immediate citations of the published year.

• Journal of Information Management
• /
• v.36 no.3
• /
• pp.183-193
• /
• 2005

Korean Academy of Medical Sciences began developing Korean Medical Citaton Index(KoMCI) database in 2002, and has announced the impact factors of Korean medical journals published since 2000. In July 2005, Korea Research Foundation also announced the KCI impact factor of journals covering all subject areas for the 2003 and 2004. We compared the impact factor(IF), impact factor excluding self-citation(ZIF), and self-citation impact factor(SIF) of KoMCI 2004 and KCI 2004 in order to disclose why there is such a great difference in the values of impact factors between two databases. Out of 72 medical journals in both database, 59 journals were compared after excluding the missing data in KCI. Mean IF of KoMCI 2004 was 0.2 and that of KCI 2004 was 0.03(p=0.0000). Mean ZIF of KoMCI was 0.06 and that of KCI was 0.01(p=0.000). Mean SIF of KoMCI was 0.139 and that of KCI was 0.02(p=0.0000). We presumed that the major difference in the impact factor values was originated from the fact that KCI does not control the authority of journal names cited in the references. We strongly recommend that it is necessary to control the authority especially if Korea Research Foundation wants to ensure the validity and reliability of KCI data in the evaluation of korean journals.

• Asian Journal of Innovation and Policy
• /
• v.2 no.2
• /
• pp.194-211
• /
• 2013

This paper introduces the Korea Citation Index (KCI) and also some macro statistics of KCI. KCI started service since 2008 by the National Research Foundation of Korea (NRF), but the data has been gathered from 1998. Our findings are as follows: heavy reliance on books in humanities, but papers as the main reference in all other disciplines. Impact factor is an increasing trend in all disciplines. Social science has the highest impact factor among all fields. In some fields even in science and engineering areas, there are more KCI papers than Korean JCR papers and impact factors of the KCI are higher than JCR. As for the distinction between nationally and internationally fields or journals, some disciplines in social science are clearly nationally oriented. NSE journals listed in both KCI and JCR, however, are not clear in terms of impact factor, but clear in terms of the numbers of papers.

• Journal of the Korean Society for Library and Information Science
• /
• v.38 no.4
• /
• pp.271-289
• /
• 2004

In this study, we analyze out citing and cited references among researchers, using KSCI (Korean Science Citation Index) database that is developed by KISTI. we generate and analyze that impact factor and immediate index with same method in JCR's. KSCI's impact factor and immediate index compared to JCR's, and with this basis, this study propose the need of development KSCI database and present new service model for evaluate of domestic journals.

• Journal of the Korean Society for information Management
• /
• v.32 no.4
• /
• pp.205-221
• /
• 2015

The impact of a journal is commonly used as the impact of an individual paper within that journal. It is problematic to interpret a journal's impact as a single paper's impact of the journal, so there are several researches to measure a single paper's impact with its own citation counts. This study applied 8 impact indicators to Korean Citation Index database and examined discipline bias of each indicator. Analyzed indicators are simple citation counts, PageRank, f-value, CCI, c-index, single publication h-index, single publication hs-index, and cl-index. PageRank has the least discipline bias at highly ranked papers and journal bias in a discipline. On the contrary, simple citation counts showed strongly biased results toward a certain discipline or a journal. KCI database provides only simple citation counts. It needs to show PageRank (global indicator) to discover influential papers in diverse areas. Furthermore it needs to consider to provide the best of local indicators. Local indicators can be calculated only with papers in users' search results because they uses citation counts of citing papers and the number of references. They are more efficient than global indicators which explore the whole database. KCI should also consider to provide Cl-index (local indicator).