Abstract
Nowadays, user-generated content has become a centerpiece in Web 2.0. People do not only navigate the web, but they also contribute content to the Internet. Among other things, they write their thoughts and opinions on many topics in forums, social networks, blogs and other websites. These opinions constitute a valuable resource for businesses, governments and consumers. In the last years, some researchers have proposed automated systems, mostly domain-independent ones, to extract structured representations of opinions contained in those texts. In this work, we propose a domain-adaptable approach to the feature-based opinion extraction task. The results confirm that domain-specific knowledge is a useful resource in order to build precise opinion extraction systems.