A brand wants to know if reviews are positive or negative. Which technique fits?
Why D is the answer
Sentiment analysis
Sentiment analysis classifies the opinion expressed in text.
In detail
- Sentiment analysis tells you whether text is positive or negative.
- Sample results to check that it reads your domain well.
Use case
An illustrative scenario, not a real incident.
A brand tracks how customers feel. Sentiment analysis marks each review positive or negative, and the trend appears on a dashboard.
See it in different ways
flowchart LR A["Text"] --> B["Keyword extraction: main terms"] A --> C["Entity recognition: people, places"] A --> D["Sentiment: positive or negative"] A --> E["Summarization: shorter version"]
mindmap
root((AI workloads))
Text
Sentiment
Key phrases
Entities
Speech
Recognition
Synthesis
Vision
Classification
Object detection
OCR
Documents
Information extraction
Generative
Text
Imagesflowchart TD
Q{"What do you want to know?"}
Q -->|"How they feel"| A0["Sentiment analysis"]
Q -->|"What they mention"| A1["Keyword extraction"]Key point: Positive or negative means sentiment analysis.
Why the other options are wrong
- A. Optical character recognition
- OCR reads text from images.
- B. Keyword extraction
- Keyword extraction finds terms, not opinion.
- C. Translation into a second language
- Translation changes the language.