Visitor Sentiment and Behavioral Analytics: Leveraging NLP to Continuously Improve Hajj and Umrah Services - Abdelrahman Sheta, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
Hajj and umrah pilgrimages attract multitude of visitors every single year making the management of services very complicated and providing satisfaction to the visitors. This paper will examine how Natural Language Processing (NLP) and behavioral analytics can be applied to continuously rescue and enhance the experience of pilgrims. Observeing the posts on social media, the evaluation of surveys and data on the interaction in the digital field, the study determines the trends of sentiment, behavior, and aspects of service enhancement. Based on the results, AI-based analytical models would help generate actionable insights to improve the operational efficiency, spiritual and cultural experiences as well as overcome ethical, legal, and privacy issues related to AI implementation. This research aims to make a contribution to the existing body of the literature by providing evidence-based system to sustain and visitor-centric management of the Hajj and Umrah services taking note of the interplay of technology, spirituality and courageous service advancement.
Keywords: Hajj; Umrah; Natural Language Processing (NLP); Visitor Sentiment; Behavioral Analytics; Artificial Intelligence (AI); Service Optimization; Religious Tourism