This document discusses using opinion mining and sentiment analysis of user reviews to generate personalized and compelling explanations for recommender systems. It describes extracting features and sentiment from reviews, summarizing them, and using the strength of the explanations to rank item recommendations. An evaluation using hotel data and reviews from TripAdvisor found that ranking recommendations based on explanation strength prioritized better options with more pros and fewer cons compared to ranking by average review ratings alone.