Department of General History, Bar Ilan University, Ramat Gan, Israel.
Department of Information Science, Bar Ilan University, Ramat Gan, Israel.
PLoS One. 2024 Jul 22;19(7):e0307115. doi: 10.1371/journal.pone.0307115. eCollection 2024.
Citation networks enable analysis of author groups, defining in-group dynamics, and mapping out inter-group relationships. While intellectual diversity and inclusiveness is one of the important principles of modern scholarship, it is intriguing to explore the extent to which these principles apply to historical communities of leaders and intellectuals. This paper introduces a novel methodological framework aimed at assessing the degree of viewpoint plurality and diversity of historical scholarship communities, through an in-depth analysis of the citations used in their literature, which has become possible due to the recently developed advanced computational analysis techniques. To achieve this goal, we have devised a set of new network-based indicators grounded in standard network metrics. These indicators can be applied at both the individual author and community levels. The developed methodology was applied to a citation network automatically constructed from a corpus of Rabbinic Halachic literature spanning the 10th to 15th centuries. This corpus includes over 5,000 citations from hundreds of books authored by approximately 140 Rabbinic scholars from six diverse geographic communities. We found that most of the authors and communities cite many more external resources from other communities than their own reflecting a willingness to engage with a diverse range of viewpoints. A more in-depth analysis based on the novel proportional diversity measures unveils more intriguing insights. Contrary to expectations, communities with the greatest number of external citations, such as Spain and Ashkenaz, surprisingly exhibit lower levels of viewpoint plurality compared to others, such as Italy and North Africa, elucidating a key finding of the study.
引文网络可用于分析作者群体,定义群体内部动态,并绘制群体间关系。虽然多样性和包容性是现代学术的重要原则之一,但有趣的是要探讨这些原则在多大程度上适用于历史上的领导者和知识分子群体。本文引入了一种新颖的方法框架,旨在通过深入分析文献中的引文来评估历史学术社区的观点多样性和观点多样性程度,这得益于最近开发的先进计算分析技术。为了实现这一目标,我们设计了一套基于标准网络指标的新的基于网络的指标。这些指标可以应用于个人作者和社区层面。所开发的方法应用于从 10 至 15 世纪的拉比 Halachic 文献语料库自动构建的引文网络。该语料库包含来自六个不同地理社区的大约 140 位拉比学者撰写的数百本书中的 5000 多条引文。我们发现,大多数作者和社区引用其他社区的外部资源远远多于自己的资源,反映出他们愿意与各种不同的观点接触。基于新颖的比例多样性度量的更深入分析揭示了更有趣的见解。与预期相反,拥有最多外部引文的社区,如西班牙和阿什肯纳兹,与其他社区(如意大利和北非)相比,观点多样性水平出人意料地较低,这阐明了该研究的一个关键发现。