We present a method of automaticaly extracting and gathering specific data text from web pages, creating a thematic corpus of reviews for opinion mining and sentiment analysis. The internet is an immense source of machine-readable texts [11] suitable for linguistic corpus studies [3][1]. Though, specific tools of web information extraction research domain as well as from the NLP do not include an open source system able to provide a thematic corpus according to an end-user request [16]. The need of use natural texts as databank for opinion mining and sentiment analysis is increased since the expansion of the digital interaction between users and blogs, forums and social networks. The RevScrap system is designed to provide an intuitive, easy-to-use interface able to extract specific information from accurate web pages returned by search engine's request and create a corpus composed by comments, reviews, opinions, as expressed by users' experience and feedback. The corpus is well structured in xml documents, reflected Singler's design criteria [4].