Skip to content

Generative AI & LLMs

Sentiment analysis

Using computers to estimate the attitude or feeling expressed in words.

Example

A system classifies customer comments as positive, negative or neutral.

Why people use it

It helps summarize the tone of large amounts of feedback.

What you'll hear

“Do these comments sound positive or negative?”

What this means for you

Review examples before using sentiment labels to judge people.

Can you control it?

Sometimes

Sometimes. Your choices depend on the tool and your access. The settings available to an everyday user may differ from those available to the people running it.

Common questions

Can it recognize sarcasm reliably?
Not always. The same words can express praise or criticism depending on the situation and speaker.
Can one message express mixed feelings?
Yes. Someone might praise the service while criticizing the price in the same message.
Does a negative label explain what needs fixing?
Not by itself. You still need to understand what the person was unhappy about.

Related terms

Still have questions?

Up to 500 characters.

Ask LATHIC about AI. Relevant glossary entries may be included.

Your question, the glossary entries it matches, and a rotating pseudonymous identifier go to Microsoft Azure’s OpenAI service through Vercel AI Gateway to generate an answer. Zero retention and no training are required of the provider, and LATHIC does not save your question or answer. Privacy Notice