Text analytics, also known as text mining or natural language processing, is a field of study that focuses on extracting insights and meaning from unstructured text data. It involves the use of machine learning algorithms, statistical analysis, and natural language processing techniques to identify patterns, trends, and relationships within large volumes of text data.

One common application of text analytics is sentiment analysis, which involves determining the sentiment (positive, negative, or neutral) of a piece of text. This can be useful in a variety of contexts, such as analyzing customer reviews to gauge satisfaction with a product or service, or analyzing social media posts to understand public sentiment about a particular topic or event. 

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