Analyzing sentiment in movie reviews
Sentiment analysis is the use of several different techniques, including NLP, to identify the emotional state associated with human-generated information, text in our case. In this recipe, we are going to perform sentiment analysis on real-world movie reviews. We will classify the reviews into two sentiments: positive or negative.
To achieve this, we will use several pre-trained models from GluonNLP Model Zoo, and apply its word embeddings to feed a classifier, which will output the predicted sentiment. We will apply this process to a new dataset: IMDb Movie Reviews.
Getting ready
As in previous chapters, in this recipe, we will be using a little bit of matrix operations and linear algebra, but it will not be hard at all.
Furthermore, we will be classifying text datasets. Therefore, we will revisit some concepts already seen in Recipe 4, Understanding text datasets – loading, managing, and visualizing the Enron Email dataset,...
