Bibliometric analysis is crucial for evaluating scientific publications, traditionally relying on metrics like citation count, SCI/SSCI article, and journal impact factor (IF). However, these methods often face bias and limitations. Despite the IF's dominance for over 50 years, there's no consensus on alternatives. Recent studies emphasize the need for comprehensive metrics, such as the disruption score, which evaluates how a publication challenges existing knowledge. Unfortunately, the disruption index also has some logical issues and requires the development of more effective and advanced evaluation metrics. The importance of bibliometric analysis in fields like health and business management highlights the need for standardized methodologies. This research topic aims to explore evolving bibliometric indicators to enhance research impact assessment beyond traditional metrics.
With the continuous application of bibliometric indicators, many questionable results have emerged. For example, the top ten institutions in the Nature Index are mostly Chinese institutions, but there are very few Nobel laureates from China. There are significant differences in the consistency of university rankings among QS, THE, USNews, and ShanghaiRanking. Similarly, there are dramatic differences in the results of Scopus' high cited scholars, Clarivate Analytics' highly cited researchers, and the world's top 2% of scientists jointly released by Stanford University and Elsevier. Although significant flaws in the original disruption index were identified in 2019, the metric has nevertheless continued to be widely cited. What are the fundamental reasons for these differences and conflicts? Are these evaluation systems too arbitrary in the selection of indicators and the adoption of methods? This Research Topic aims to explore the problems behind these evaluation methods from a quantitative or qualitative perspective and further identify possible solutions, such as better indicators, more appropriate methods, and more effective comprehensive analysis models.
We invite scholars to contribute original research articles, brief research reports, reviews, mini reviews, and methods. The specific themes to be explored, include, but are not limited to the following:
• Comparative analysis of traditional analysis indicators and new evaluation indicators (H index, Eigenfactor, Altmetric Attention Score, etc) • In depth analysis of the disruptive index and its derivative indicators • Developing new indicators to evaluate the scientific contribution of a publication • Constructing a comprehensive analysis model for evaluating the scientific value of a publication • Research on the application of solo citations in discovering disruptive achievements • Exploration of limitations in indicators and analysis methods in common ranking systems • Research on the application of standardized academic evaluation methods in fields like health and business management.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Conceptual Analysis
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
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Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
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