Understanding the Basics of Text Classification

Text classification is the task of assigning a set of predefined labels to text. Given a set of predefined classes and some text, you want to understand which predefined class this text falls into. We have to determine the classes ourselves by the nature of our data before starting the classification task. For example, a customer review can be positive, negative, or neutral.

Text classifiers are used for detecting spam emails in your mailbox, determining the sentiment of customer's reviews, understanding customer's intent, sorting customer's complaint tickets, and so on.

Text classification is a fundamental task of NLP. It is gaining importance in the business world as it enables businesses to automate their processes. One immediate example is spam filters. Every day, users receive many spam emails, but most of the time never see these emails and don't get any notifications because spam filters save the users from bothering about irrelevant emails and from spending time deleting these emails.

Text classifiers can come in different flavors. Some classifiers focus on the overall emotion of the text, some classifiers focus on detecting the language of the text, and some classifiers focus on only some words of the text, such as verbs. The following are some of the most common types of text classification and their use cases:

• Topic detection: Topic detection is the task of understanding the topic of a given text. For example, the text in a customer email could be asking about a refund, asking for a past bill, or simply complaining about the customer service.

• Sentiment analysis: Sentiment analysis is the task of understanding whether the text contains positive or negative emotions about a given subject. Sentiment analysis is often used to analyze customer reviews about products and services.

• Language detection: Language detection is the first step of many NLP systems, such as machine translation.

The following figure shows a text classifier for a customer service automation system: