[논문]Meta-Analysis of Associations Between Classic Metric and Altmetric Indicators of Selected LIS Articles

Vysakh, C.; Babu, H. Rajendra

doi:10.1633/jistap.2022.10.4.5

Meta-Analysis of Associations Between Classic Metric and Altmetric Indicators of Selected LIS Articles 원문보기

Journal of information science theory and practice : JISTaP, v.10 no.4, 2022년, pp.53 - 65

Vysakh, C. (Department of Studies and Research in Library and Information Science, Tumkur University) , Babu, H. Rajendra (Department of Studies and Research in Library and Information Science, Tumkur University)

Abstract ▼ AI-Helper

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.

주제어

표/그림 (9)

그림 lu Fig. 1. PRISMA (Preferred Re-In c meta-analysis (n=8)porting Items for System-atic Reviews and Meta-analyses) flow diagram.
표 Table 1. Characteristics/details of the articles selected for the study (including excluded studies)
표 Table 1. Continued
표 Table 1. Continued
그림 Fig. 2. Forest plot for the metaanalysis.
그림 Fig. 3. Meta-analysis of articles from Web of Science.
그림 Fig. 4. Meta-analysis of articles from Google Scholar.
표 Table 2. Pooled correlation and heterogeneity
그림 Fig. 5. Funnel plot for publication bias.

AI 본문요약
AI-Helper

제안 방법

The review question is framed to determine the PCOR between classic metric and altmetric indicators of the LIS articles that satisfies the eligibility criteria.

성능/효과

no. 10) estimated at -.106 as per the Spearman correlation indexed on Google Scholar could also be a possible reason.
No potential conflict of interest relevant to this article was reported.
30). The possible reason for this could be that the articles indexed in the Web of Science subjected to analysis include higher samples than those indexed in Google Scholar. In addition, the negative correlation of one article (Art.
The symmetry of the diagram shows that no publication bias existed, and Egger’s (p-value=0.82) and Begg’s test (p-value=0.25) confirmed the same since the p-value stood higher than 0.05 (p>0.05).
2) for LIS articles. Thus it can be concluded that for LIS articles, the AAS and other significant indicators, i.e., Mendeley and Twitter, show similar characteristics to traditional citation metric indicators. Thus it can be used as a proxy for measuring the immediate invisible impact of LIS research articles.
When we carried out the sub-group analysis based on the source of citations, we discovered that articles indexed on the Web of Science showed a higher PCOR (0.41) than articles indexed in Google Scholar (0.30). The possible reason for this could be that the articles indexed in the Web of Science subjected to analysis include higher samples than those indexed in Google Scholar.

후속연구

Furthermore, a comprehensive meta-synthesis should be conducted between classic and social metric indicators to understand the existing friction better. Similar meta-analyses or syntheses can be conducted in other domains to understand whether altmetrics exhibits the same feature as classic metrics.

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