Introduction
The Teneo platform is delivered with a collection of agile, customizable tools that build on the usual intent recognition that natural language systems offer. Combined with Teneo's unique infrastructure, these tools allow you to cumulatively monitor various aspects of user behavior during a conversation:
| Characteristics of user input | Categories | Examples |
| Sentiment | negative positive |
not happy about this that was a nice answer |
| Intensity cues | capitalization duplication emojis punctuation intensifying vocabulary multiple one-word sentences |
what DAY is this I know, I know :-) what?? what!! what!?! very good, extremely well You. are. great. |
| Abusive language | hate speech profanity violence sexual abuse |
(clearly racist statements) (obscene language) (threats of violence) (explicit sexual references) |
| Controversial themes |
abortion crime death fascism sex suicide terrorism |
I need an abortion. How do I rob a bank? My best friend died. Heil Hitler. Let’s have sex. I want to end it all. What happened on 9/11? |
Think about these categories for a moment. Knowing what happens at the meta-level of a conversation opens numerous powerful possibilities. During the session, you have an opportunity to identify and react to various situations that arise, tailoring the conversation towards a better user experience. After the session, you are able to analyze user sentiment towards company products and services as well as towards acceptance of the system's handling of the users’ issues. In this article, we focus on use cases for sentiment tracking during the session.