Example of chatbot app that includes sentiment analysis application

One such chatbot is the WhatsApp Bot with Sentiment Analysis using Python and Twilio (https://www.twilio.com/blog/build-whatsapp-bot-sentiment-analysis-python-twilio).

This bot can detect when the user is unhappy and redirect them to a live agent. The bot uses the TextBlob library to perform sentiment analysis on the user's messages and assigns a polarity score between -1 and 1, where -1 is very negative and 1 is very positive.

The bot also uses a threshold value to determine when the user's sentiment is too low and needs human intervention. The bot then sends a message to the user asking if they want to talk to a live agent, and if the user agrees, the bot connects them to a Twilio phone number that routes the call to the agent.

This is an example of how chatbot sentiment analysis can improve customer satisfaction and provide empathetic service.

Reference:

https://www.twilio.com/blog/build-whatsapp-bot-sentiment-analysis-python-twilio