Building a sentiment analyzer

Sentiment analysis is the process of determining the sentiment of a given piece of text. For example, it can 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 is generally used to get a sense of how people feel about a particular 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 classifier. We first need to 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 we divide the text data into training and testing datasets, we will train the Naive Bayes classifier...