Lexical, sentiment and correlation analysis of sacred writings. A tale of cultural influxes and different ways to interpret reality

Abstract

Natural Language Processing (NLP) has transformative potential for decoding sacred writings, bridging linguistic and temporal relationships between cultures. These texts, laden with cultural and religious significance. The study analyzes texts from 14 belief systems using lexical, sentiment and correlation assessment. The analysis revealed that sacred texts are complex due to archaic language, but tend to show similar themes, historical contexts, and emotional tones. The study highlights common terms found throughout the texts, but also revealing specific terms that are influenced by the cultural context of the belief system. It also explores the various depictions of fauna and flora, uncovering the impact of spatio-temporal contexts on the composition of sacred writings. Sentiment analysis reveals polarity variations between cultures and suggest conflicts of style during translation of the texts. Comparative analysis uncovers text clusters with high similarity and cultural influences between religions that coexisted. This work showcases NLP’s potential to enhance comprehension of sacred texts and promote cross-cultural understanding.