What is text mining?
Text mining is a research practice that involves using computers to discover information in large amounts of unstructured text.
Unstructured text is data not formatted according to an encoding structure like HTML or XML.
Examples of unstructured data used for text mining include journal and news articles, blog posts, and email.
Researchers use text mining tasks such as:
- sentiment analysis
- named entity extraction
- document summarization
By using these methods, researchers can make connections and draw conclusions about the content of large text corpora.
Questions? Ask Us!
If you have questions about text mining tools, techniques, or resources, reach out to UMKC Libraries Digital Scholarship Services for a research consultation.
Sources for Text Data
Here are some sources where you can find text data. If you need text data from one of the Library's subscription databases, please email umkcdss@umkc.edu and we can help you get started.
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