# Sentiment Analysis

Sentiment analysis (or opinion mining) is a [natural language processing (NLP)](https://monkeylearn.com/natural-language-processing/) technique used to determine whether data is positive, negative or neutral. Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiment in [customer feedback](https://monkeylearn.com/customer-feedback/), and understand customer needs.

### What Is Sentiment Analysis? <a href="#what-is-sentiment-analysis" id="what-is-sentiment-analysis"></a>

Sentiment analysis is the process of detecting positive or negative sentiment in text. It’s often used by businesses to detect sentiment in social data, gauge brand reputation, and understand customers.

### Types of Sentiment Analysis <a href="#types-of-sentiment-analysis" id="types-of-sentiment-analysis"></a>

Sentiment analysis focuses on the polarity of a text (_positive, negative, neutral_) but it also goes beyond polarity to detect specific feelings and emotions (_angry, happy, sad_, etc), urgency (_urgent, not urgent_) and even [intentions](https://monkeylearn.com/blog/intent-classification/) (_interested v. not interested_).

**Graded Sentiment Analysis**

**Emotion detection**

**Aspect-based Sentiment Analysis**
