This master thesis is focused on the development of a system for automatically processing a large database of textual hotel reviews in natural language to extract relevant opinions from users on a series of predefined features of quality (service, food, location, etc) The information extracted has to be categorized according to polarity (positive/negative opinions) and arranged so that the final search application can use it to display complementary information of each hotel based on the extracted opinions. Initially a set of hotel reviews is data mined from online sources; a subset of this dataset is then filtered and manually annotated to create a corpus and to help with the creation of a taxonomy for the domain of hotel reviews. A system is then designed to detect, extract and evaluate opinions, and evaluated using the corpus built.