Mining the Sentiment Expectation of Nouns Using Bootstrapping Method

We propose an unsupervised bootstrapping method to generate a new type of affect knowledge base: the sentiment expectation of nouns (e.g., “high salary” is desirable while “high price” is usually undesirable, because people have opposite sentiment expectation towards “salary” and “price”). A bootstrapping framework is designed to retrieve patterns that might be used to express complaints from the Web. The sentiment expectation of a noun could be automatically predicted with the output patterns. We evaluate the retrieved patterns and show that our method yields good results. Also, they are applied to improve both sentence and document level sentiment analysis results.