Use this action to automatically detect positive or negative language or feelings present within an email, document or block of text.
- Analyze inquiries from customers, use this action to flag negative sentiment to prioritize responses and route the inquiry to the most appropriate representative
- Analyze customer comments over time to determine a customer satisfaction score
- Include sentiment and magnitude in a predictive model to categorize or prioritize inquiries
Sentiment analysis supports the following languages:
|Portuguese (Brazilian & Continental)||pt|
- The text for which you would like to calculate sentiment. Typically, you will reference a field for this.
The output of this action is the sentiment and magnitude score for the analyzed text and the predicted language. For example, the text “clearly positive” has a sentiment score of .8 and magnitude of 3.0. Other examples:
|Text for analysis||Sentiment||Magnitude|
- Overall emotion of the text on a scale from -1.0 (very negative) to 1.0 (very positive)
- How much emotional content is present within the document, which is usually proportional to the length of the document
- The language of the text using an ISO 639-1 code, for example en for English or de for German
- Use task conditions to determine actions that should occur based on sentiment and magnitude scores
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