Sentiment Analysis and Topic Modeling

In this study, I will be exploring over 68k customer reviews of over 720 mobile phones posted on Amazon. I aim to take a two-pronged approach. One, to use the techniques of topic modeling to point out the top positive and negative aspects of purchase that the users associate with a brand / product based on their reviews. In this respect, we will focus on the application of LDA (Latent Dirichlet Allocation) and NMF (Non-Matrix Factorization) towards achieving this goal and then comparing the outputs obtained by these two techniques The second prong of the project will be pointed at creating a predictive model to predict user ratings by exploring logistic regression, Support Vector Machine, Random Forest and Naïve Bayes and arrive at the best model to do the same.