Characterizing pandemic-related publications: a retrospective study using spatial citation network analysis
Abstract The COVID-19 pandemic sparked a surge in research across disciplines, offering vital knowledge for addressing the crisis and earning widespread citations. Yet, the spatiotemporal patterns within these citation networks are underexplored. This study uses network analysis to examine pandemic-...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | Computational Urban Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43762-025-00184-y |
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