Text analysis (TA) is a machine learning technique used to automatically extract valuable insights from unstructured text data. Companies use text analysis tools to quickly digest online data and documents, and transform them into actionable insights.
Text analytics is used for deeper insights, like identifying a pattern or trend from the unstructured text. For example, text analytics can be used to understand a negative spike in the customer experience or popularity of a product.
Text analysis is really the process of distilling information and meaning from text. For example, this can be analyzing text written in reviews by customers on a retailer’s website or analyzing documentation to understand its purpose.
How does machine learning text analysis work?
- Gather the data. Decide what information you will study and how you will collect it.
- Prepare the data. Unstructured data needs to be prepared or preprocessed.
- Apply a machine learning algorithm for text analysis. You can write your algorithm from scratch or use a library.