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

• Journal of Information Science Theory and Practice
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• v.11 no.4
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• pp.40-50
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• 2023

Research in interdisciplinary fields like biomechanics is published in a variety of journals whose visibility depends on bibliometric indexing that is often driven by citation analysis of bibliometric databases. This study documented variation in publication metrics and research subject categories assigned to 14 biomechanics journals. Authors, citation, and citation rate (CR) were collected for the top 15 cited articles in the journals retrieved from the Google Scholar service. Research subject categories were also extracted for journals from three databases (Dimensions, Journal Citation Reports, and Scopus). Despite the focus on biomechanics for the journals studied, these biomechanics journals have widely varying CR and subject categories assigned to them. There were significant (p=0.001) and meaningful (77-108%) differences in median CR between average, low, and high CR groups of these biomechanics journals. Since CR are primary data used to calculate most journal metrics and there is no one biomechanics subject category, field normalization for journal citation metrics in biomechanics is difficult. Care must be taken to accurately interpret most citation metrics of biomechanics journals as biased proxies of general usage of research, given a specific database, time frame, and area of biomechanics research.

• Journal of Information Science Theory and Practice
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• v.10 no.4
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• pp.53-65
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• 2022

Altmetrics or alternative metrics gauge the digital attention received by scientific outputs from the web, which is treated as a supplement to traditional citation metrics. In this study, we performed a meta-analysis of correlations between classic citation metrics and altmetrics indicators of library and information science (LIS) articles. We followed the systematic review method to select the articles and Erasmus Rotterdam Institute of Management Guidelines for reporting the meta-analysis results. To select the articles, keyword searches were conducted on Google Scholar, Scopus, and ResearchGate during the last week of November 2021. Eleven articles were assessed, and eight were subjected to meta-analysis following the inclusion and exclusion criteria. The findings reported negative and positive associations between citations and altmetric indicators among the selected articles, with varying correlation coefficient values from -.189 to 0.93. The result of the meta-analysis reported a pooled correlation coefficient of 0.47 (95% confidence interval, 0.339 to 0.586) for the articles. Sub-group analysis based on the citation source revealed that articles indexed on the Web of Science showed a higher pooled correlation coefficient (0.41) than articles indexed in Google Scholar (0.30). The study concluded that the pooled correlation between citation metrics with altmetric indicators was positive, ranging from low to moderate. The result of the study gives more insights to the scientometrics community to propose and use altmetric indicators as a proxy for traditional citation indicators for quick research impact evaluation of LIS articles.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.249-277
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• 2023

The purpose of this study is to explore the potential contribution of citation metrics to improving the search performance of citation index databases. To this end, the study generated ten queries in the field of library and information science and conducted experiments based on the relevance assessment using 3,467 documents retrieved from the Web of Science and 60,734 documents published in 85 SSCI journals in the field of library and information science from 2000 to 2021. The experiments included re-ranking of the top 100 search results using citation metrics and search methods, query expansion experiments using vector space model retrieval systems, and the construction of a citation-based re-ranking system. The results are as follows: 1) Re-ranking using citation metrics differed from Web of Science's performance, acting as independent metrics. 2) Combining query term frequencies and citation counts positively affected performance. 3) Query expansion generally improved performance compared to the vector space model baseline. 4) User-based query expansion outperformed system-based. 5) Combining citation counts with suitability documents affected ranking within top suitability documents.

• Clinical and Experimental Reproductive Medicine
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• v.41 no.4
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• pp.147-150
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• 2014

Objective: Clinical and Experimental Reproductive Medicine (CERM) converted its language to English only beginning with the first issue of 2011. From that point in time, one of the goals of the journal has been to become a truly international journal. This paper aims to identify the position of CERM in its scholarly journal network based on the journal's metrics. Methods: The journal's metrics, including citations, countries of author affiliation, and countries of citing authors, Hirsch index, and proportion of funded articles, were gathered from Web of Science and analyzed. Results: The two-year impact factor of 2013 was calculated at 0.971 excluding self-citation, which corresponds to a Journal Citation Reports ranking of 85.9% in the category of obstetrics and gynecology. In 2012, 2013, and 2014, the total citations were 17, 68, and 85, respectively. Authors from nine countries contributed to CERM. Researchers from 25 countries cited CERM in their articles. The Hirsch index was six. Out of 88 original articles, 35 studies received funds (39.8%). Conclusion: Based on the journal metrics, changing the journal language to English was found to be successful in promoting CERM to international journal status.

• Journal of Information Science Theory and Practice
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• v.3 no.2
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• pp.16-30
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• 2015

The term megajournal is used to describe publication platforms, like PLOS ONE, that claim to incorporate peer review processes and web technologies that allow fast review and publishing. These platforms also publish without the constraints of periodic issues and instead publish daily. We conducted a yearlong bibliometric profile of a sample of articles published in the first several months after the launch of PeerJ, a peer reviewed, open access publishing platform in the medical and biological sciences. The profile included a study of author characteristics, peer review characteristics, usage and social metrics, and a citation analysis. We found that about 43% of the articles are collaborated on by authors from different nations. Publication delay averaged 68 days, based on the median. Almost 74% of the articles were coauthored by males and females, but less than a third were first authored by females. Usage and social metrics tended to be high after publication but declined sharply over the course of a year. Citations increased as social metrics declined. Google Scholar and Scopus citation counts were highly correlated after the first year of data collection (Spearman rho = 0.86). An analysis of reference lists indicated that articles tended to include unique journal titles. The purpose of the study is not to generalize to other journals but to chart the origin of PeerJ in order to compare to future analyses of other megajournals, which may play increasingly substantial roles in science communication.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.53-69
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• 2021

This study aims to understand the research landscape of South Korea using the data of 2020 Google Scholar Metrics. To achieve the goal, we constructed and analyzed four types of networks including the university collaboration network, the keyword co-occurrence network, the journal citation network, and the discipline citation network. Through the analysis of the university collaboration network, we found major universities such as Seoul National University, Keimyung University, and Sungkyunkwan University that have led collaborative research. Job related keywords such as job change intention and job satisfaction have been frequently studied with other keywords. Through the analysis of the journal citation network, we found multiple journals such as The Journal of the Korea Contents Association, Korean Journal of Sociology, and Korean Journal of Culture and Social Issues that have been widely cited by the other journals and influenced them. Finally, Education, Business administration, and Social welfare were identified as the top influential disciplines that have influenced other disciplines through the knowledge diffusion. The study is the first of its kind to use the data of Google Scholar Metrics and conduct a stepwise network analysis (e.g., keyword, journal, and discipline) to broadly understand the research landscape of South Korea. Our results can be used by government agencies and universities to develop effective strategies of promoting university collaboration and interdisciplinary research.

• 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 information Management
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• v.40 no.2
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• pp.59-80
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• 2023

Traditional models for categorizing researcher types have mostly utilized research output metrics. This study proposes a new model that classifies researchers based on the characteristics of research collaboration. The model uses only research collaboration indicators and does not rely on citation data, taking into account that citation impact is related to collaborative research. The model categorizes researchers into four types based on their collaborative research pattern and scope: Sparse & Wide (SW) type, Dense & Wide (DW) type, Dense & Narrow (DN) type, Sparse & Narrow (SN) type. When applied to the quantum metrology field, the proposed model was statistically verified to show differences in citation indicators and co-author network indicators according to the classified researcher types. The proposed researcher type classification model does not require citation information. Therefore, it is expected to be widely used in research management policies and research support services.

• 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.