• KSLA Bulletin
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• s.2
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• pp.16-27
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• 2010

Recently, the valuation of research papers has been greatly emphasized, and their citation has been accepted as a very useful indicator. In this study, we performed correlation analyses between the paper citation counts and 11 explanatory variables of morphological and conceptual factors with a test dataset of the papers of 11 journals in library and information science. The analysis results of the correlations show that only the document similarity has 5% or more standardized variances(r2) with paper citation counts and the document similarity with citation counts get higher as the variable value increases.

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

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.149-154
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• 2017

Objectives: The purpose of this study is to analyze the co-author networks in the Journal of the Korean Academy of Child and Adolescent Psychiatry, a representative journal published by a branch of the domestic psychiatric academy, in order to present the current state of the co-authoring of and developments in child and adolescent psychiatry. Methods: We visualized and estimated the basic characteristics of the co-author networks shown by 564 authors who wrote 251 papers published in the Journal of the Korean Academy of Child and Adolescent Psychiatry between 2005 and 2015, in order to assess their network characteristics, author centrality, and relevance to research performance. Results: The co-author networks in the Journal of the Korean Academy of Child and Adolescent Psychiatry showed the characteristics of a small world and scale-free network. There was a correlation between the author centrality within the network and the research performance of the authors, but less correlation was shown between the centrality and mean paper citation counts. Conclusion: The network structure in the Journal of the Korean Academy of Child and Adolescent Psychiatry showed similarity to the co-authoring of other branches. However, given that the mean paper citation counts were less correlated with the author centrality than those in other branches, it may be necessary to promote an increase in the mean paper citation counts.

• Journal of Korean Library and Information Science Society
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• v.50 no.3
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• pp.23-47
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• 2019

In order to ascertain disciplinary differences in publication patterns that can help improve assessment of research performance in Korea, we analyzed the bibliometric data of six disciplines from Korea Citation Index. Results showed differences in research size, competitiveness, productivity, impact, and collaboration among disciplines. Disciplines in science were the largest in terms of author and institution followed by humanities and social science, but humanities produced the most publications per author, followed by social science and science disciplines. Sociology publications received most citation per paper but humanities received most citations per author, which was greatly influenced by the number of co-authors per paper. Distribution of author counts per paper varied widely across disciplines. Humanities were dominated by single-author publications, whereas the majority of publications in sciences were co-authored. The study also highlighted differences in citation lag time and illustrated differences in distribution and impact of core authors and institutions across disciplines.

• Journal of Korean Library and Information Science Society
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• v.49 no.2
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• pp.245-266
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• 2018

This study proposes a novel method to rank highly-cited papers that incorporate the likelihood of receiving future citations. Instead of using the total citation count, the proposed method ranks most-papers based on the yearly citation growth rate (YCGR). The rank of YCGR can be obtained by calculating the average ranks of five individual citation related variables: 1) Total Citation Count, 2) Leftside-Slope, 3) Publication Year, 4) Peak Year, and 5) Rightside-Slope. To empirically test the proposed method, yearly citation counts with other relevant bibliographic records of the 50 most-cited papers in Library and Information Science (LIS) journals used in the study conducted by Walters and Wilder were collected from the Scopus database for the years 1996 to 2016. The result indicated that the YCGR appears to reflect the degree to which the paper is likely to receive future citations, and the ranked list based YCGR offered an alternative viewing feature of the highly-cited papers in LIS. Although more empirical analyses are needed, the rank based on YCGR in conjunction with variables related to YCGR can be used as an alternative method in recognizing influential papers in LIS.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.165-169
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• 2017

Altmetrics is an emergent research area whereby social media is applied as a source of metrics to evaluate scientific impact. Recently, the interest in altmetrics has been growing. Traditional scientific impact evaluation indictors are based on the number of publications, citation counts and peer reviews of a researcher. As research publications were increasingly placed online, usage metrics as well as webometrics appeared. This paper explores the potential benefits of altmetrics and the deep relationship between each metrics. Firstly, we found a weak-to-medium correlation among the 11 altmetrics and visualized such correlation. Secondly, we conducted principal component analysis and exploratory factor analysis on altmetrics of social media, divided the 11 altmetrics into four feature sets, confirming the dispersion and relative concentration of altmetrics groups and developed the altmetrics evaluation model. We can use this model to evaluate the scientific impact of articles on social media.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.1
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• pp.105-123
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• 2007

The aim of this paper is to analyse correlation between the national competitiveness and research competitiveness in OECD countries. As the result of correlation analysis there are positive correlations among competitiveness indicators(GERD, SCI articles, average citation counts, JCR journal titles, patents). And SCI articles and peer-reviewed journals emanating from the developed countries or the OECD is essential to maintaining national and research competitiveness in Korea. This study also calls for further correlation analysis between research competitiveness and academic libraries.

• Journal of Information Science Theory and Practice
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• v.5 no.3
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• pp.48-60
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• 2017

The purpose of this paper is to understand the profiles of users and their motivations in sharing research articles on Twitter. The goal is to contribute to the understanding of Twitter as a new altmetric measure for assessing impact of research articles. In this paper, we extended the previous study of tweet motivations by finding out the profiles of twitter users. In particular, we examined six characteristics of users: gender, geographic distribution, academic, non-academic, individual, and organization. Out of several, we would like to highlight here three key findings. First, a great majority of users (86%) were from North America and Europe indicating the possibility that, if in general, tweets for research articles are mainly in English, Twitter as an alternative metric has a Western bias. Second, several previous altmetrics studies suggested that tweets, and altmetrics in general, do not indicate scholarly impact due to their low correlation with citation counts. This study provides further details in this aspect by revealing that most tweets (77%) were by individual users, 67% of whom were nonacademic. Therefore, tweets mostly reflect impact of research articles on the general public, rather than on academia. Finally, analysis from profiles and motivations showed that the majority of tweets (from 42% to 57%) in all user types highlighted the summary or findings of the article indicating that tweets are a new way of communicating research findings.