Facet-based opinion retrieval from blogs

The paper presents methods of retrieving blog posts containing opinions about an entity expressed in the query. The methods use a lexicon of subjective words and phrases compiled from manually and automatically developed resources. One of the methods uses the Kullback-Leibler divergence to weight subjective words occurring near query terms in documents, another uses proximity between the occurrences of query terms and subjective words in documents, and the third combines both factors. Methods of structuring queries into facets, facet expansion using Wikipedia, and a facet-based retrieval are also investigated in this work. The methods were evaluated using the TREC 2007 and 2008 Blog track topics, and proved to be highly effective. Keywords Opinion retrieval, information retrieval, blogs, sentiment analysis.

• Type: Journal
• Year: 2010
• Where: IPM
• Authors: Olga Vechtomova
• Keywords: IPM 2010, Paper Presents Methods, Query Terms, Subjective Words