Using text mining to uncover hidden information in historical sources

В статье представлен обзор того, как интеллектуальный анализ текста используется для выявления скрытой информации в исторических текстах. Внимание акцентируется на методе тематического моделирования и моделях эмбеддингов слов. Статья иллюстрирует, как эти методы использовались в конкретных исторических исследованиях. Делается вывод о том, что интеллектуальный анализ текста является полезным инструментом для обнаружения скрытой информации в исторических текстах.The article presents an overview of how text mining can be employed to reveal hidden information in historical texts. The attention is focused on the method of thematic modeling and word embedding models. The article illustrates how these techniques have been utilized in historical research. It concludes that text mining is a useful tool for uncovering hidden information in historical

A Corpus Approach to Roman Law Based on Justinian’s Digest

Traditional philological methods in Roman legal scholarship such as close reading and strict juristic reasoning have analysed law in extraordinary detail. Such methods, however, have paid less attention to the empirical characteristics of legal texts and occasionally projected an abstract framework onto the sources. The paper presents a series of computer-assisted methods to open new frontiers of inquiry. Using a Python coding environment, we have built a relational database of the Latin text of the Digest, a historical sourcebook of Roman law compiled under the order of Emperor Justinian in 533 CE. Subsequently, we investigated the structure of Roman law by automatically clustering the sections of the Digest according to their linguistic profile. Finally, we explored the characteristics of Roman legal language according to the principles and methods of computational distributional semantics. Our research has discovered an empirical structure of Roman law which arises from the sources themselves and complements the dominant scholarly assumption that Roman law rests on abstract structures. By building and comparing Latin word embeddings models, we were also able to detect a semantic split in words with general and legal sense. These investigations point to a practical focus in Roman law which is consistent with the view that ancient law schools were more interested in training lawyers for practice rather than in philosophical neatness.</jats:p

Vir is to Moderatus as Mulier is to Intemperans. Lemma Embeddings for Latin

This paper presents a new set of lemma embeddings for the Latin language. Embeddings are trained on a manually annotated corpus of texts belonging to the Classical era: different models, architectures and dimensions are tested and evaluated using a novel benchmark for the synonym selection task. A qualitative evaluation is also performed on the embeddings of rare lemmas. In addition, we release vectors pre-trained on the “Opera Maiora” by Thomas Aquinas, thus providing a resource to analyze Latin in a diachronic perspective