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Sentiment analysis is a subfield of Machine Learning (ML) and Natural Language Processing (NLP) that deals with extracting thoughts, opinions, or sentiments from the voice or textual data.
It includes real time narrative mapping that allows your chatbot to identify the important words in a sentence and assign them a relative value of positive, neutral, objective, or negative, giving the bot an understanding of the entire tenor of the conversation. In short, sentiment analysis helps in developing the bot’s emotional intelligence.
While ML helps to personalize the chatbot’s performance by harnessing historical customer data, NLP helps to evaluate and interpret the information sent by the customer in real-time.
These two features collectively help chatbots to deliver relevant responses and conduct meaningful conversations.
You can update the list by adding words to make your bot smarter to capture the user sentiments closely and make conversations effective.