Select Analysis tab on the Text Analyzer form

The text analytics functionality of the Pega 7 Platform provides an array of linguistic, statistical and machine learning techniques for gathering, sorting, classifying, and researching various types of social media content.

The text analytics tools include the following types of analysis:

• Sentiment analysis - Determines the opinion or attitude of a person with respect to the overall contextual polarity of a document (for example, a Facebook post, tweet, email, and so on).
• Classification analysis - Assigns one or more categories to a document by using various taxonomies.
• Entity extraction analysis - Identifies named text features, such as people, organizations, place names, and abbreviations.

You can test the accuracy of the analysis with the testing tool provided as part of the Text Analyzer rule form to fine-tune the configuration and make and receive results that have a high accuracy score.

You can access the results of the analysis through the Data-NLP-Outcome rule.

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