Datasets for bibliometric analysis of regulatory T cells in gastric cancer (2005-2025)

<p dir="ltr"><b>Description:</b><br>This dataset supports the findings of the bibliometric review article titled "Global Research Landscape of Regulatory T Cells in Gastric Cancer: A Comprehensive Bibliometric Analysis (2005-2025)". It contains the process...

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Auteur principal: Houshu Tu (22026668) (author)
Autres auteurs: Jing Hong (50544) (author), Menglin Chen (2071006) (author), Panpan Zhu (714514) (author), Ling He (282204) (author)
Publié: 2025
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Description
Résumé:<p dir="ltr"><b>Description:</b><br>This dataset supports the findings of the bibliometric review article titled "Global Research Landscape of Regulatory T Cells in Gastric Cancer: A Comprehensive Bibliometric Analysis (2005-2025)". It contains the processed and cleaned data used to generate all analyses, figures, and tables in the manuscript.</p><p dir="ltr"><b>Data Source:</b><br>The raw data was retrieved from the Web of Science Core Collection (WoSCC) on October 15, 2025.</p><p dir="ltr"><b>Dataset Contents:</b></p><ol><li><code><strong>Cleaned_Bibliometric_Data.txt</strong></code>: The primary dataset containing the full collection of 464 publications after deduplication and cleaning. Key fields include: Title, Authors, Journal, Publication Year, Abstract, Author Keywords, WoS Categories, Citation Count, and Reference List.</li><li><code><strong>Top_10_Percent_Cited_Articles.txt</strong></code>: A subset of the 50 most-cited publications (approximately the top 10%) used for the high-impact publication analysis. Includes all fields from the primary dataset plus additional categorization.</li></ol><p dir="ltr"><b>Methodology:</b><br>Data cleaning and standardization were performed using R and Bibliometrix. The datasets provided here are the final, analysis-ready versions used as input for VOSviewer, CiteSpace, and Bibliometrix to create the co-authorship networks, keyword co-occurrence maps, and citation analyses presented in the manuscript.</p><p dir="ltr"><b>Usage Notes:</b><br>These datasets can be used to replicate the study's findings, serve as a baseline for future bibliometric studies in immuno-oncology, or be integrated with other data sources for expanded analyses.</p>