What is Sentiment Analysis?

Sentiment Analysis, explained

Sentiment analysis classifies the emotional tone of text such as reviews, social media posts, survey responses, or support tickets. Older approaches relied on lists of positive and negative words. Modern systems use machine learning and language models, which better handle context, negation, and mixed opinions.

A restaurant group might run sentiment analysis over thousands of online reviews each month to see whether complaints about wait times are rising at a particular location. Support teams use it to flag angry messages for faster response. Results are useful for spotting trends but less reliable for individual messages, because sarcasm, slang, and cultural differences can confuse models. Combining sentiment scores with topic categories usually gives more actionable insight than an overall score alone.