Analyzing Sentiment and Actionability with Content Analyzer
This topic describes part of the functionality of Genesys Content Analyzer.
You can use Genesys Content Analyzer to analyze the sentiment and actionability of interactions that have been brought into the system by Genesys Social Messaging Management. Genesys supplies samples which demonstrate these capabilities.
To deploy the sentiment sample, use the following procedure.
- In Configuration Manager or Genesys Administrator, create a language called English_Sentiment.
- With Knowledge Manager set to that language, import the file EnglishSentiment.kme, which is located in the <KnowledgeManagerHome>\SentimentModel directory.
- A model SentimentSampleModel for analyzing sentiment.
- The training object Sentiment that created that model.
- A category tree SentimentDetection that contains the categories to assign to interactions as a result of the analysis.
To use the actionability sample, import the file Actionability.kme, which is located in the <KnowledgeManagerHome>\ActionabilityModel directory.
- A model Actionability for analyzing actionability.
- The training object Actionability that created that model.
- A category tree Actionability that contains the categories to assign to interactions as a result of the analysis.
You can use the sample training objects to produce new models, improving the quality by making adjustments such as:
- Altering the settings such as those for quality level. See Step 4 of the Procedure: Scheduling training using the Model Options tab and Cross-Validation.
- Using the Mail Editor to edit the content of the messages in the training object. See Step 3 of Creating New E-mails Manually.
- Using the Mail Editor to add more sample messages to the training object.
Genesys also provides sample screening rules for detecting sentiment and actionability.
For more information on Genesys Social Messaging Management, see the eServices Social Media Solution Guide, available on the eServices product page.