What feature would you use to filter reviews to determine if people like or dislike a business?

Sentiment analysis is a powerful feature used to evaluate and understand the feelings expressed in text, making it particularly effective for determining whether people have positive or negative opinions about a business. When applied to customer reviews, sentiment analysis examines the language used and assigns a sentiment score that categorizes the overall review as positive, negative, or neutral. This allows businesses to gauge customer satisfaction and identify areas for improvement based on public perception.

In contrast, key phrase extraction focuses on identifying significant terms and phrases within a body of text, rather than assessing the sentiment behind them. Similarly, entity recognition involves identifying and classifying key entities in the text (such as names, organizations, locations) but does not provide insight into the sentiments associated with those entities. Intent classification, on the other hand, identifies the intent behind user input or queries, which is useful in understanding user needs but does not directly analyze whether the sentiment expressed towards a business is favorable or unfavorable.

Overall, sentiment analysis is the most effective tool for filtering reviews to ascertain the general sentiment of the public regarding a business.