Sentiment analysis involves classifying comments or opinions in text into categories such as "positive" or "negative" often with an implicit category of "neutral". A classic sentiment application would be tracking what people think about different topics. Sentiment analysis in data science and machine learning is also called "opinion mining" or in marketing terminology "voice of the customer". It can be a very useful tool to check the affinity to brands, products, or domains. Sentiment analysis is extremely useful in social media monitoring as it allows us to get an overview of the wider public opinion behind specific topics.
Sentiment analysis also has its limitations and is not to be used as a 100% accurate marker.
As natural language can be very ambiguous with multiple connotations, it's hard if not impossible...
