Combining corpus and thesaurus information for extracting sentiment words

The paper describes a combined approach to extraction of a domain-specific sentiment lexicon. At first, an initial version of a domain-specific lexicon is obtained by application of a supervised model. At the second stage, the ordered list of sentiment words is refined using the thesaurus information. This combined model is applied to several domains and at last, the domain-specific sentiment lexicons are united to create an improved version of the Russian sentiment lexicon in the generalized domain of products.