Visualization of rank-citation curves for fast detection of h-index anomalies in university metrics
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866929222104121344 |
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| author | Nazarovets, Serhii |
| author_facet | Nazarovets, Serhii |
| contents | University rankings, despite facing criticism, continue to maintain their popularity. In the 2023 Scopus Ranking of Ukrainian Universities, certain institutions stood out due to their high h-index, despite modest publication and citation numbers. This phenomenon can be attributed to influential research topics or involvement in international collaborative research. However, these results may also be due to the authors' own efforts to increase the number of citations of their publications in order to improve their h-index. To investigate this, the publications from the top 30 universities in the ranking were analysed, revealing humpback rank-citation curves for two universities. These humpbacks indicate unusual trends in the citation data, especially considering the high percentage of self-citations and FWCI of analysed papers. While quantitative analysis has limitations, the combination of humped rank-citation curves, self-citations, FWCI, and previous research findings raises concerns about the possible causes of these anomalies in the citation data of the analysed universities. The method presented in this paper can aid ranking compilers and citation databases managers in identifying potential instances of citation data anomalies, emphasizing the importance of expert assessment for accurate conclusions. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2401_13490 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Visualization of rank-citation curves for fast detection of h-index anomalies in university metrics Nazarovets, Serhii Digital Libraries University rankings, despite facing criticism, continue to maintain their popularity. In the 2023 Scopus Ranking of Ukrainian Universities, certain institutions stood out due to their high h-index, despite modest publication and citation numbers. This phenomenon can be attributed to influential research topics or involvement in international collaborative research. However, these results may also be due to the authors' own efforts to increase the number of citations of their publications in order to improve their h-index. To investigate this, the publications from the top 30 universities in the ranking were analysed, revealing humpback rank-citation curves for two universities. These humpbacks indicate unusual trends in the citation data, especially considering the high percentage of self-citations and FWCI of analysed papers. While quantitative analysis has limitations, the combination of humped rank-citation curves, self-citations, FWCI, and previous research findings raises concerns about the possible causes of these anomalies in the citation data of the analysed universities. The method presented in this paper can aid ranking compilers and citation databases managers in identifying potential instances of citation data anomalies, emphasizing the importance of expert assessment for accurate conclusions. |
| title | Visualization of rank-citation curves for fast detection of h-index anomalies in university metrics |
| topic | Digital Libraries |
| url | https://arxiv.org/abs/2401.13490 |