Building a sentiment analyzer

Sentiment analysis is the process of determining the sentiment of a piece of text. For example, it can be used to determine whether a movie review is positive or negative. This is one of the most popular applications of natural language processing. We can add more categories as well, depending on the problem at hand. This technique can be used to get a sense of how people feel about a product, brand, or topic. It is frequently used to analyze marketing campaigns, opinion polls, social media presence, product reviews on e-commerce sites, and so on. Let's see how to determine the sentiment of a movie review.

We will use a Naive Bayes classifier to build this sentiment analyzer. First, extract all the unique words from the text. The NLTK classifier needs this data to be arranged in the form of a dictionary so that it can ingest it. Once the text data is divided into training and testing datasets, the Naive Bayes classifier will be trained...