This session will discuss the findings of two studies conducted to explore user-generated content in public library catalogues, and its potential contribution to readers’ advisory (RA) services. The session will explore how user content, in the form of tags and reviews, provides a rich data set that connects to traditional RA access points. Further, the session will discuss the creation of three taxonomies for memory, emotion and mood based on user content, and the use of these taxonomies to enhance discovery and the reading experience.