Abstract
The Questio de aqua et terra is a cosmological treatise traditionally attributed to Dante Alighieri. However, the authenticity of this text is controversial, due to discrepancies with Dante's established works and to the absence of contemporary references. This study investigates the authenticity of the Questio via computational authorship verification (AV), a class of techniques which combine supervised machine learning and stylometry. We build a family of AV systems and assemble a corpus of 330 13th- and 14th-century Latin texts, which we use to comparatively evaluate the AV systems through leave-one-out cross-validation. Our best-performing system achieves high verification accuracy (F1=0.970) despite the heterogeneity of the corpus in terms of textual genre. The key contribution to the accuracy of this system is shown to come from Distributional Random Oversampling (DRO), a technique specially tailored to text classification which is here used for the first time in AV. The application of the AV system to the Questio returns a highly confident prediction concerning its authenticity. These findings contribute to the debate on the authorship of the Questio, and highlight DRO's potential in the application of AV to cultural heritage.
Abstract (translated)
《水与地的问题》是一篇传统上归于但丁·阿利吉耶里的宇宙学著作。然而，由于该文本与但丁已知作品存在矛盾以及缺乏同时代的引用证据，其真实性备受争议。本研究通过计算作者身份验证（AV）方法来探讨《水与地的问题》的真实性。这种方法结合了监督机器学习和文体测量技术。我们构建了一组AV系统，并汇集了一个包含330篇13世纪至14世纪拉丁文文本的语料库，利用留一交叉验证法对这些系统进行比较评估。性能最佳的系统实现了高准确率（F1=0.970），尽管语料库在文体类型方面存在多样性。该系统准确性提高的关键在于分布随机过采样技术（DRO），这是一种专门用于文本分类的方法，首次在此领域应用于AV研究中。我们将AV系统应用到《水与地的问题》上，得到一个关于其真实性的高度自信的预测结果。这些发现有助于作者身份争议的讨论，并突显了DRO在文化遗产领域的AV应用潜力。
URL
https://arxiv.org/abs/2501.05480
