提出融合相似性与网络关系的多样性包容度量新方法。
Diversity and Inclusion Index with Networks and Similarity: Analysis and its Application
- 基于相似性与网络连接构建多样性包容指数
- 通过真实数据验证指标与外部指标强相关
- 适用于社会、生物等领域多元分析
近年来，'多样性'与'包容性'在社会与生物等多个领域受到广泛关注。要全面理解这些概念，不仅需考察类别数量，还需分析类别间的相似性与关系。本文提出一种考虑相似性与网络连接的新多样性包容指数，分析了该指数的性质，并利用已有的多样性与网络度量探讨其数学关系。同时，提出基于多样性效用的相似性估计方法，以及可视化比例、相似性与网络连接的方案。最后，通过真实世界数据评估了该指标与外部度量的相关性，证实所提指数可有效应用。本研究推动了对多样性与包容性分析的更精细理解。
原文摘要 · Abstract (English)
In recent years, the concepts of ``diversity'' and ``inclusion'' have attracted considerable attention across a range of fields, encompassing both social and biological disciplines. To fully understand these concepts, it is critical to not only examine the number of categories but also the similarities and relationships among them. In this study, I introduce a novel index for diversity and inclusion that considers similarities and network connections. I analyzed the properties of these indices and investigated their mathematical relationships using established measures of diversity and networks. Moreover, I developed a methodology for estimating similarities based on the utility of diversity. I also created a method for visualizing proportions, similarities, and network connections. Finally, I evaluated the correlation with external metrics using real-world data, confirming that both the proposed indices and our index can be effectively utilized. This study contributes to a more nuanced understanding of diversity and inclusion analysis.
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