Sentiment Analysis of a Translated Text of the Qur’ān Using the Pareto Principle

Abstract

Islamic scholars have made several efforts to translate the Qur’ān into various languages of the world, with English being the most prominent target language. This article uses textual analysis to study translated verses of the Qur’ān and shows that the predominant result of subjectivity analysis was objectivity by a contribution of 63% with a preponderant non-ironic tone. There is a close balance between the topic categories of entity and concept in the sentiment analysis and agreement in different textual elements polarity of 72% unipolarity. Interestingly, the verses with positive polarity outweigh those with negative polarity, with a significant number of verses reflecting non-polar texts. A topic sentiment analysis of the verses showed the prevalence of non-polarity over the positive, negative, neutral, strong positive, then strong negative polarity. Sūrat al-Baqarah holds the greatest polarity count. This investigation paves the way for a series of in-depth analyses for the examination of religious texts. Also, it sheds light on the necessity of the control of the language translation of verses to deliver the same or close impression to that of the original religious text. Refinement of the text analysis algorithm may be required in the quality control of the translation. Nevertheless, the current study provides direct evidence of the future ability of this type of program to derive conclusions from religious texts in an acceptable manner.