The revolution of natural language processing via large language models has motivated its use in multidisciplinary areas that include social sciences and humanities and more specifically, comparative religion. Sentiment analysis provides a mechanism to study the emotions expressed in text. Recently, sentiment analysis has been used to study and compare translations of the Bhagavad Gita, which is a fundamental and sacred Hindu text. In this study, we use sentiment analysis for studying selected chapters of the Bible. These chapters are known as the Sermon on the Mount. We utilize a pre-trained language model for sentiment analysis by reviewing five translations of the Sermon on the Mount, which include the King James version, the New International Version, the New Revised Standard Version, the Lamsa Version, and the Basic English Version. We provide a chapter-by-chapter and verse-by-verse comparison using sentiment and semantic analysis and review the major sentiments expressed. Our results highlight the varying sentiments across the chapters and verses. We found that the vocabulary of the respective translations is significantly different. We detected different levels of humour, optimism, and empathy in the respective chapters that were used by Jesus to deliver his message.

翻译：大型语言模型引发的自然语言处理革命推动了其在多学科领域的应用，包括社会科学和人文学科，特别是比较宗教学。情感分析为研究文本中表达的情感提供了一种机制。近期，情感分析已被用于研究和比较印度教核心神圣文本《薄伽梵歌》的不同译本。本研究采用情感分析法对《圣经》选章展开研究，这些章节被称为“登山宝训”。我们通过考察《登山宝训》的五个译本——包括钦定版、新国际版、新修订标准版、兰姆萨版和基础英语版——运用预训练语言模型进行情感分析，逐章逐节地开展情感与语义对比研究，并系统梳理所表达的主要情感。研究结果突显了各章各节间的情感差异。我们发现不同译本的词汇存在显著差异，并检测到耶稣在传递信息时所使用的各章中蕴含不同程度的幽默、乐观与同理心。