Hi Lee,
The ability for users to provide their own words / phrases that indicate negative / positive /neutral sentiment is a roadmap item.
Currently, the Sentiment Analysis capability within Genesys Cloud has been trained from a data set of millions of external/general samples and then fine tuned from actual contact center interactions.
Note that the word "brilliant" on its own may not represent positive sentiment. The same is true about "anger" being negative. The model uses it's neutral network to determine if the words / phrase actually represents a negative / positive sentiment in contact center conversations. It may be that the system sees it as positive, but not positive enough to tag it.
If you are interested in getting more analysis on this, you can provide your calls through Customer Care who can pass them on to our Data Scientists to give you more insight on why certain phrasing has not resulted in a positive / negative marking. This may also help in tuning our global model.
Hope that helps.
Thanks,
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Rakesh Tailor
Director, Product Management - Workforce Engagement
Genesys Cloud
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