Yelp Reviews text analysis

In this scenario I’m leading a new branded hotel and need to know what customers who give poor reviews of hotels tend to bring up. To minimize poor service, my analytics will examine hotel reviews using topic modeling to identify what reviewers who give poor reviews actually write about in their experience to ensure your hotel focuses special attention and ensures high-quality services in those domains.

Using python packages such as LdaModel, stopwords, word_tokenize, and CoherenceModel I wanted to answer questions like:

What topics do reviewers tend to bring up in general?

How do happy customers differ from unhappy customers in the topics they bring up in their review?

Are there other characteristics about customers that would be useful to know about?

Want to see the find product and the python code? Click the button below to go to the GitHub repository!