  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.
