What is text mining?
Text mining refers to a practice that involves using computers to discover information in large amounts of both structured and unstructured text., Accordingly, unstructured text is data not formatted according to an encoding structure like HTML or XML, while the structured text is seemingly organized into CSV files or SQL database.
Examples of data used for text mining include Twitter, journal and news articles, blog posts, and email.
Researchers use text mining tasks such as:
By using these methods, researchers can make connections and draw conclusions about the content of large text corpora.
The image on the right is one example of what you can do with text mining.
Why do text mining?
Text mining helps researchers detect patterns and connections in large volumes of textual material.
The objective in text mining is to find previously unknown data, something that has yet to be understood and could not have written down yet. Text mining enables researchers to draw conclusions from large volumes of material they would not be able to otherwise read, synthesize, and incorporate into their scholarship.
Researchers in fields ranging from chemical sciences to the humanities have begun using text mining to detect patterns and discover unknown information.
On-line Text Mining / Text Analytics Tool
Commercial Text Mining / Text Analytics Software
Free and Open-Source Text Mining / Text Analytics Software