A natural language processing–driven map of the aging research landscape (IMAGE)
Caption
Figure 6. Mapping underexplored connections in the aging research literature through semantic overlap analysis. (A) Heatmap of average TF-IDF score of the top 20 most significant words from each cluster when evaluated against documents in every other cluster using the dataset containing all documents. Rows represent the source clusters from which the top 20 words were selected based on their TF-IDF score. Columns represent the target clusters where the mean TF-IDF scores of these words were computed. Color represents the magnitude of the average TF-IDF score. (B) Top 3 most and least studied relationships among clusters (all documents). (C) Heatmap of average TF-IDF score of the top 20 most significant words from each BoA cluster when evaluated against documents in every other BoA cluster using the dataset containing only BoA-related clusters. Rows represent the source clusters from which the top 20 words were selected based on their TF-IDF score. Columns represent the target clusters where the mean TF-IDF scores of these words were computed. Color represents the magnitude of the average TF-IDF score. (D) Top 3 most and least studied relationships among BoA clusters.
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Copyright: © 2025 Perez-Maletzki and Sanz-Ros. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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