If you are looking for review datasets for opinion analysis tasks, there are quite a few out there. Please see an updated list in my text mining blog. Here are some that I am familiar with:
||This is a collection of movie reviews used for various opinion analysis tasks; You would find reviews split into positive and negative classes as well as reviews split into subjective and objective sentences.
||Pang & Lee
|Multi–Domain Sentiment Dataset
||Products (books, dvds..)
||Product reviews from Amazon.com covering various product types (such as books, dvds, musical instruments). The data has been split into positive and negative reviews. There are more than 100,000 reviews in this dataset. The reviews come with corresponding rating stars.
||Blitzer et. al
||Hotels & Products
||Reviews from Amazon.com and TripAdvisor. It contains attributes such as author name, content, date and the ratings.
||Wang et. al
||Hotels, Cars, Electronics
||Topic related sentences extracted from user reviews. You will find 51 topics with approximately 100 sentences each (on average). The reviews were obtained from multiple sources – Tripadvisor (hotels), Edmunds.com (cars) and Amazon.com (various electronics).
||Ganesan et. al
||Hotels & Cars
||Reviews of cars and and hotels collected from Tripadvisor (~259,000 reviews) and Edmunds (~42,230 reviews). For cars, the extracted fields include dates, author names, favorites and the full textual review. For hotels, the fields include date, review title and the full review.
||Ganesan & Zhai
||Contains a total 52077 reviews. The fields contain rating information, review counts, percent and cuisine type