Multilingual natural language processing approach for linguistic and philosophical analysis of the Bhagavad Gita

Abstract This paper seeks to investigate the use of Natural Language Processing techniques in analyzing the Bhagavad Gita, a fundamental text in Hindu philosophy that has stood the test of time and centuries of interpretation and analysis. Through the use of techniques such as topic modeling and sentiment analysis, the paper reveals the major themes in the text: devotion, duty, knowledge, and renunciation, as well as the emotions expressed in the conversation between Arjuna and Krishna. The originality of this paper lies in the use of a multi-lingual system of natural language processing, whereby the original Sanskrit text and English and Tamil translations of the text are analyzed to facilitate cross-linguistic interpretation of the text while retaining the semantic and emotive nuances. The pre-processing techniques such as tokenization, stemming, lemmatization, and POS tagging are used to prepare the text for thorough analysis and ensure thorough and accurate findings. Visualization of the frequency of words using techniques such as word clouds also aids in understanding the concepts in the text. The research also underscores the universal relevance of the Gita, making it a relevant text for comparative religious studies. This research has implications for a number of disciplines, including digital humanities, comparative religious studies, interfaith dialogue, and artificial intelligence-based research. The research underscores the potential of NLP to uncover the intricacies of meaning embedded in holy scriptures, providing new insights into their philosophical and emotional content.

Authors

Publication Details

Journal
Discover Computing
Published
2026-05-02
DOI
https://doi.org/10.1007/s10791-026-10111-2
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multilingual natural language processing approach for linguistic and philosophical analysis of the Bhagavad Gita

K. Sampath Kumar, J. Jayanthi
Discover Computing
Sentiment Analysis and Opinion Mining
article

Multilingual natural language processing approach for linguistic and philosophical analysis of the Bhagavad Gita

K. Sampath Kumar, J. Jayanthi
article en

Abstract

Abstract This paper seeks to investigate the use of Natural Language Processing techniques in analyzing the Bhagavad Gita, a fundamental text in Hindu philosophy that has stood the test of time and centuries of interpretation and analysis. Through the use of techniques such as topic modeling and sentiment analysis, the paper reveals the major themes in the text: devotion, duty, knowledge, and renunciation, as well as the emotions expressed in the conversation between Arjuna and Krishna. The originality of this paper lies in the use of a multi-lingual system of natural language processing, whereby the original Sanskrit text and English and Tamil translations of the text are analyzed to facilitate cross-linguistic interpretation of the text while retaining the semantic and emotive nuances. The pre-processing techniques such as tokenization, stemming, lemmatization, and POS tagging are used to prepare the text for thorough analysis and ensure thorough and accurate findings. Visualization of the frequency of words using techniques such as word clouds also aids in understanding the concepts in the text. The research also underscores the universal relevance of the Gita, making it a relevant text for comparative religious studies. This research has implications for a number of disciplines, including digital humanities, comparative religious studies, interfaith dialogue, and artificial intelligence-based research. The research underscores the potential of NLP to uncover the intricacies of meaning embedded in holy scriptures, providing new insights into their philosophical and emotional content.

Discover ComputingVol. 29(1)
Quality Education
Openalex Percentile: Top 6%
Sentiment Analysis and Opinion Mining
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.