From Vajrayana Tara to Bengali Baul: A Computational Study of Lexical Transmission Across Buddhist, Shakta, and Vaishnava Traditions in Bengal
Summary
A computational corpus study analyzed vocabulary relationships across eight Bengali and Sanskrit devotional literature traditions from the 8th to 19th centuries, including Buddhist Vajrayana, Shakta Tantra, Vaishnava, and Baul. Researchers used TF-IDF character n-gram vectorization and cosine similarity on 75 texts to quantify the historical claim of Buddhist Vajrayana vocabulary absorption into Shakta Tantra. A central finding reveals that 12th-century Bridge Tara texts (Buddhist-Shakta transitional) exhibit a 0.54 cosine similarity to Shakta Kali texts, an 8.5-fold contrast compared to the 0.0 similarity of Vaishnava Gitagovinda texts. This demonstrates the specificity of Buddhist-Shakta lexical transmission. Furthermore, Brihannilatantra Tara texts show Shakta-to-Buddhist vocabulary ratios of 2.0 to 4.0, and Ramprasad Sen's 18th-century Kali songs contain 56 occurrences of "Tara" alongside 103 of "Kali." The study also found Vaishnava Bengali tradition contributes to modern Baul vocabulary (0.29 similarity), slightly less than the Buddhist Sahajiya chain (0.31). These results offer the first quantitative evidence for Buddhist-Shakta syncretism in Bengal.
Key takeaway
For research scientists studying historical linguistic evolution, this computational approach offers a robust method to quantify previously unquantified claims of lexical transmission. You can apply TF-IDF character n-gram vectorization and cosine similarity to corroborate syncretic processes across diverse textual corpora. This allows you to move beyond qualitative arguments, providing measurable evidence for cultural exchange and vocabulary absorption in historical datasets. Consider integrating similar quantitative methods into your next historical linguistics project.
Key insights
Computational linguistics can quantitatively corroborate historical claims of lexical transmission and syncretism across religious traditions.
Principles
- Lexical similarity can quantify historical cultural transmission.
- Specificity tests validate cross-tradition vocabulary absorption.
- Character n-grams effectively capture linguistic shifts.
Method
A corpus of 75 texts was analyzed using TF-IDF character n-gram vectorization. Cosine similarity then quantified vocabulary relationships across eight devotional traditions.
In practice
- Apply n-gram vectorization to historical text analysis.
- Use cosine similarity to measure vocabulary overlap.
- Quantify cultural exchange in other historical contexts.
Topics
- Computational Linguistics
- Lexical Transmission
- TF-IDF
- Cosine Similarity
- Historical Linguistics
- Religious Syncretism
- Bengali Literature
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Editorial summary, takeaway, and curation by AIssential. Original article published by Computation and Language.