# sarcasm recognition
**Wikidata**: [Q124149528](https://www.wikidata.org/wiki/Q124149528)  
**Source**: https://4ort.xyz/entity/sarcasm-recognition

## Summary
Sarcasm recognition is a topic within sentiment analysis focused on identifying sarcastic language in text. It is treated as a subclass of sentiment analysis, which uses natural language processing, text analysis, and computational linguistics to identify and extract subjective information from source materials.

## Key Facts
- Sarcasm recognition is a subclass of **sentiment analysis**.
- Sentiment analysis is defined as the use of **natural language processing, text analysis, and computational linguistics** to identify and extract **subjective information** in source materials.
- Sarcasm recognition is categorized as a **topic** (per the provided description).
- Sarcasm recognition is explicitly listed as being **part of / parented by** sentiment analysis.
- The parent class **sentiment analysis** has a referenced **sitelink_count of 27** (as provided in the source material).

## FAQs
### Q: What is sarcasm recognition?
A: Sarcasm recognition is the identification of sarcasm in language, treated as a topic within sentiment analysis. It falls under sentiment analysis methods that use NLP, text analysis, and computational linguistics to extract subjective information.

### Q: Is sarcasm recognition part of sentiment analysis?
A: Yes. The provided classification states sarcasm recognition is a subclass of sentiment analysis and is listed under sentiment analysis as its parent.

### Q: What field does sarcasm recognition belong to?
A: It belongs to sentiment analysis. Sentiment analysis uses natural language processing, text analysis, and computational linguistics to identify and extract subjective information in source materials.

### Q: What does sentiment analysis do in relation to sarcasm recognition?
A: Sentiment analysis provides the broader framework for extracting subjective information from text. Sarcasm recognition is a specialized topic within that framework.

## Why It Matters
Sarcasm recognition matters because it is positioned as a specialized area within sentiment analysis, a field that applies natural language processing, text analysis, and computational linguistics to identify and extract subjective information from source materials. Since sarcasm is a form of subjective expression, recognizing it fits directly into the broader goal of sentiment analysis: understanding and extracting subjective content from text. As a subclass of sentiment analysis, sarcasm recognition represents a more specific focus area that sits under an established computational approach to language. This classification helps practitioners and researchers place sarcasm recognition within the broader landscape of language understanding tasks that deal with subjectivity. In practical terms, treating sarcasm recognition as part of sentiment analysis clarifies its relationship to other sentiment-focused methods and highlights that it is concerned with interpreting subjective meaning in text rather than purely objective content.

## Notable For
- Classified as a **subclass of sentiment analysis**.
- Explicitly linked to a parent category defined by **NLP, text analysis, and computational linguistics** methods.
- Associated with the extraction of **subjective information** (via its parent class, sentiment analysis).
- Identified as a distinct **topic** within the sentiment analysis domain.

## Body
### Classification
- **Entity:** sarcasm recognition
- **Type (from description):** Topic
- **Subclass of:** sentiment analysis
- **Part of / Parent:** sentiment analysis

### Relationship to Sentiment Analysis
- Sarcasm recognition is placed under **sentiment analysis** as a subclass.
- The parent class, sentiment analysis, is described as:
  - The use of **natural language processing**.
  - The use of **text analysis**.
  - The use of **computational linguistics**.
  - The goal of identifying and extracting **subjective information** in source materials.

### Source-Provided Metadata
- The parent class **sentiment analysis** includes a provided **sitelink_count: 27**.