Preview: Sentiment analysis model
[This topic is pre-release documentation and is subject to change.]
The sentiment analysis prebuilt model detects positive or negative sentiment in text data. You could use it to analyze social media, customer reviews, or any text data you want to analyze. Sentiment analysis evaluates text input, and gives scores and labels at a sentence and document level. The scores and labels can be positive, negative, and neutral. At the document level, there can also be a mixed sentiment label, which has no score. The sentiment of the document is determined by aggregating the sentence scores.
Use in Power Automate
If you want to use this prebuilt model in Power Automate, you can find more information in Use sentiment analysis model in Power Automate.
Supported language and data format
- Documents can't exceed 5,120 characters.
- For information on language support, see Language and region support for the text analytics API.
If text is detected, the sentiment analysis model will output the following information:
- DocumentScores: Value in the range of 0 to 1. Values close to 1 indicate greater confidence that the identified sentiment is accurate.
- Sentences: List of sentences from the input text with analysis of its sentiments.
- SentenceScores: Value in the range of 0 to 1. Values close to 1 indicate greater confidence that the sentiment is accurate.