In the internet era, almost every business entity is trying to have its digital footprint in digital media and other social media platforms. For these entities, word of mouse is also very important. Particularly, this is quite crucial for the hospitality sector dealing with hotels, restaurants etc. Consumers do read other consumers reviews before making final decisions. This is where it becomes very important to understand which aspects are affecting most in the minds of the consumers while giving their ratings. The current study focuses on the consumer reviews of Indian hotels to extract aspects important for final ratings. The study involves gathering data using web scraping methods, analyzing the texts using Latent Dirichlet Allocation for topic extraction and sentiment analysis for aspect-specific sentiment mapping. Finally, it incorporates Random Forest to understand the importance of the aspects in predicting the final rating of a user.

翻译：在互联网时代，几乎每个商业实体都试图在数字媒体和其他社交媒体平台上留下数字足迹。对这些实体而言，网络口碑也至关重要。特别是对于涉及酒店、餐厅等的酒店业来说，这一点尤为关键。消费者在做出最终决定前确实会阅读其他消费者的评论。因此，理解哪些方面在消费者给出评分时对其影响最大变得非常重要。本研究聚焦于印度酒店的消费者评论，旨在提取对最终评分至关重要的方面。研究涉及使用网络爬虫方法收集数据，运用潜在狄利克雷分布进行主题提取，并通过情感分析实现面向特定方面的情感映射。最后，研究采用随机森林算法来理解这些方面在预测用户最终评分时的重要性。