Saving the sentiment analysis model
In the Model selection step, export the file with the model or save the model as a Decision Data rule to use that model as part of the Pega Platform text analytics feature.
If you want to export the binary file that contains the model that you created, next to the model, click Download model file.
Complete the model creation process by clicking Create.
- Analyzing natural language
Effortlessly analyze and extract meaningful information from large volumes of text with the use of text analytics. Based on your findings, you can further improve business performance and customer experience.
- Determining the emotional tone of text
Sentiment analysis determines whether the opinion that the writer expressed in a piece of text is positive, neutral, or negative. Knowledge about customers' sentiments can be very important because customers often share their opinions, reactions, and attitudes toward products and services in social media or communicate directly through chat channels.
- Text analytics accuracy measures
Models predict an outcome, which might or might not match the actual outcome. The following measures are used to examine the performance of text analytics models. When you create a sentiment or classification model, you can analyze the results by using the performance measures that are described below.