What is Sentiment Analysis?
Quick Definition
Sentiment analysis uses AI to detect emotions and attitudes in speech or text — identifying whether a caller is happy, frustrated, urgent, or neutral — to prioritize and route calls appropriately.
Sentiment Analysis explained
Sentiment analysis (also called opinion mining or emotion AI) is a natural language processing technique that identifies and categorizes the emotional tone of spoken or written communication. In phone systems and AI receptionists, sentiment analysis processes the caller's speech in real time to detect emotional states: positive (satisfied, happy), negative (frustrated, angry, upset), neutral (informational inquiry), or urgent (emergency, time-sensitive). This capability enables intelligent call handling: frustrated callers can be immediately escalated to a manager, urgent calls can be prioritized for immediate transfer, and positive interactions can be noted for follow-up sales opportunities. Sentiment analysis also powers post-call analytics — businesses can review call sentiment trends to identify common frustrations, measure customer satisfaction over time, and train staff to handle negative interactions better. For service businesses, sentiment-aware AI receptionists can differentiate between a routine appointment request and an emergency plumbing call based on vocal urgency, routing each appropriately.
Where is sentiment analysis used?
Call centers, customer service, AI receptionists, social media monitoring.
Related terms
NLP (Natural Language Processing)
NLP is a branch of artificial intelligence that enables computers to understand, interpret, and generate human language. It powers AI receptionists, chatbots, and voice assistants.
Conversational AI
Conversational AI is technology that enables machines to understand, process, and respond to human language in natural, human-like dialogue. It powers chatbots, voice assistants, and AI receptionists.
Call Analytics
Call analytics is the measurement and analysis of phone call data — including volume, duration, peak times, outcomes, and caller demographics — to improve business performance.
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