diff --git a/docs/source/user_guide/privacy_estimation/privacy_recommender.rst b/docs/source/user_guide/privacy_estimation/privacy_recommender.rst
index f7b5305..adb7031 100644
--- a/docs/source/user_guide/privacy_estimation/privacy_recommender.rst
+++ b/docs/source/user_guide/privacy_estimation/privacy_recommender.rst
@@ -43,7 +43,7 @@ While this assumption may seem strong, it mirrors realistic scenarios where adve
 access to such data through creation of false users and webscraping.
 
 This implementation makes the assumption that each type of recommender system uses the most-popular algorithm
-to solve the cold start problem. This means that the most popular items are recommended to users
+to solve the cold start problem. This means that the candidates that are most popular are recommended to users
 who have no previous history of interaction with the system.
 
 This tool currently supports membership inference attacks in the context of collaborative filtering models.