Analyzing-Yelp-reviews-using-NLP-techniques

In this project, Yelp restaurant reviews were analysed to gain business insights using NLP techniques. Out of 6.6 million reviews, I selected only Ontario restaurants with more than 300 reviews. I divided the 1-2-star reviews as negative reviews, 3-star reviews as average review and 4-5-star reviews as positive reviews. After removing stop words and performing TF-IDF, various topic modelling approaches were used to find out relative positive, average and negative weight of topics for different restaurants. The results obtained were visualized using Tableau [1]. Moreover, I also compared the running time complexity for topic modelling using Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF). These insights would help the business owners to improve their services.