Predicting Movie Review Sentiment with Topic Models

In this blog post, the third one of our Topic Models series, we are showcasing how you can use BigML Topic Models to improve your model performance. We are using movie reviews extracted from the IMBD database to predict if a given review has a positive or a negative sentiment. Notice that in this post we will not dive into all the configuration options that BigML offers for Topic Models, for that we recommend that you read our previous post. The dataset contains 50,000 highly polarized movie reviews labeled with their sentiment class: positive or negative. This dataset was built by Stanford researchers for their paper from 2011, which achieves an accuracy of 88.89%.