APIs for Scholarly Resources

What is Text and Data Mining?

Text mining is defined as "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources", while data mining is an activity that attempts to discover interesting patterns from structured databases of facts (Hearst, 2003).

A common example of data mining is the analysis of sales records (a structured data) to determine the best time to push a sales campaign. Whereas a common example for text mining would be doing sentiment analysis on tweets on Twitter to find out more about people's reaction about a particular event.

Here's a fascinating article on the current state of TDM from a library perspective: McCracken, P. & Raub, E., (2023) “Licensing Challenges Associated With Text and Data Mining: How Do We Get Our Patrons What They Need?”, Journal of Librarianship and Scholarly Communication 11(1). doi: https://doi.org/10.31274/jlsc.15530