Computational Pathways to Intertextuality of the Ancient Indian Literature: A Multi-Method Analysis of the Maitrāyaṇī and Kāṭhaka Saṃhitās

• Published in: Journal of data mining and digital humanities Vol. NLP4DH; no. Visualisation of...
• Main Authors: Miyagawa, So, Kyogoku, Yuki, Tsukagoshi, Yuzuki, Amano, Kyoko
• Format: Journal Article
• Language: English
• Published: 07.03.2025
• ISSN: 2416-5999; 2416-5999
• DOI: 10.46298/jdmdh.15085

This paper examines semantic similarity and intertextuality in selected texts from the Vedic Sanskrit corpus, specifically the Maitrāyaṇī Saṃhitā (MS; Amano 2009) and Kāṭhaka Saṃhitā (KS). Three computational methods are employed: Word2Vec for word embeddings, the stylo package for stylometric analysis, and TRACER for text reuse detection. By comparing various sections of the texts at different granularities, patterns of similarity and structural alignment are uncovered, providing insights into textual relationships and chronology. Word embeddings capture semantic similarities, while stylometric analysis reveals clusters that differentiate the texts. TRACER identifies parallel passages, indicating probable instances of text reuse. Our multi-method analysis corroborates previous philological studies, suggesting that MS.1.9 aligns with later editorial layers, akin to MS.1.7 and KS.9.1. The findings highlight the potential of computational methods in studying ancient Sanskrit literature, complementing traditional approaches, and emphasize that smaller chunk sizes are more effective for detecting intertextual parallels. These approaches expand methodological frontiers in Indology and illuminate new research pathways for analyzing ancient texts.