درخت حوزه‌های تخصصی

As data and context continue to expand, a vast amount of textual content, including books, blogs, and papers, is produced and distributed electronically. Analyzing such large amounts of content manually is a time-consuming task. Automatic detection of feelings and emotions in these texts is crucial, as it helps to identify the emotions conveyed by the author, understand the author's writing style, and determine the target audience for these texts. The Qur’an, regarded as the word of God and a divine miracle, serves as a comprehensive guide and a reflection of human life. Detecting emotions and feelings within the content of the Qur’an contributes to a deeper understanding of God's commandments. Recent advancements, particularly the application of transformer-based language models in natural language processing, have yielded state-of-the-art results that are challenging to surpass easily. In this paper, we propose a method to enhance the accuracy and generality of these models by incorporating syntactic features such as Parts Of Speech (POS) and Dependency Parsing tags. Our approach aims to elevate the performance of emotion detection models, making them more robust and applicable across diverse contexts. For model training and evaluation, we utilized the Isear dataset, a well-established and extensive dataset in this field. The results indicate that our proposed model achieves superior performance compared to existing models, achieving an accuracy of 77% on this dataset. Finally, we applied the newly proposed model to recognize the feelings and emotions conveyed in the Itani English translation of the Qur’an. The results revealed that joy has the most significant contribution to the emotional content of the Holy Qur’an. 

  The level of satisfaction of individuals with life is one of the important criteria in the ideal lifestyle, and "mutual satisfaction" is one of the crucial manifestations of "satisfaction with life." Speaking of "satisfaction" in bilateral relationships implies the presence of both "Rāḍī" (well- pleased) and "Marḍīyy" (pleasing) aspects for both sides of these relationships. Considering the presence or absence of these two qualities in interpersonal relationships, three conceivable assumptions are possible: 1) Both parties are "Rāḍī" with each other, hence each party is also "Marḍīyy" with the other; 2) Only one of the parties is pleased with the other, therefore one is "Rāḍī" and the other is "Marḍīyy"; 3) Both parties are not "Rāḍī" with each other, hence neither is "Marḍīyy" with the other. The best case is the first assumption, and the worst case is the third assumption. When we find ourselves in the third situation, we must strive to at least transform it into the second assumption and then elevate the second assumption to the first assumption. But how is this transformation possible? The present study suggests that in one's interactions with others, instead of expecting to find oneself "Rāḍī," one should try to "Rāḍī" the other and let oneself become "Marḍīyy" with the other; because in order to be "Rāḍī" with the other, we do not have control over all the factors that lead to satisfaction, as we cannot determine or change the behaviors of the other party according to our desires. However, everyone has the choice and actions are up to them and can act according to the desires of the other party. If both parties in all bilateral relationships follow this recommendation, they will reach the ideal situation (the first assumption), which means being "Rāḍī and Marḍīyy at the same time."