# What is Sentiment Analysis? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Natural Language Processing  
> **Canonical Citation:** [https://spidits.com/ai-glossary/sentiment-analysis](https://spidits.com/ai-glossary/sentiment-analysis)

## Definition
Sentiment Analysis is an NLP task that uses classification models to identify and extract subjective information (positive, negative, or neutral tones) from text datasets.

## Architectural Mechanics & Deep Dive
Sentiment analysis is an NLP task that classifies the emotional tone of a text document (such as customer reviews, support tickets, or social media posts) into categories like positive, negative, or neutral. While traditional approaches used rule-based lexicon matchers, modern sentiment analysis utilizes fine-tuned Transformer models to capture context, sarcasm, and nuance.

## Industry Applications & Real-World Use Cases
Brand monitor tracking, customer review sorting, and algorithm trading signals

## Frequently Asked Questions

### How do models evaluate sentiment?
By mapping text to features (embeddings) and passing them to classifiers trained on labeled datasets of positive/negative text.

### Can LLMs perform sentiment analysis?
Yes, LLMs perform sentiment analysis at zero-shot or few-shot accuracy, capturing complex sarcasm better than classical algorithms.

## Related Terminology
- [nlp](https://spidits.com/ai-glossary/nlp)
- [supervised-learning](https://spidits.com/ai-glossary/supervised-learning)
- [zero-shot-learning](https://spidits.com/ai-glossary/zero-shot-learning)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*