A MODEL TO EXTRACT SENTIMENTAL KNOWLEDGE IN A SEMANTIC WEB CONTEXT

Nowadays, in a social and semantic context, the web contains millions of data, generic information and opinions. The semantic techonology, using specific ontologies, is very important to represent the web knowledge and to understand the meaning of online textual information. To extract useful knowledge and sentiment (positivity or negativity) of opinions it is necessary to have a model that interpreters this information from both semantic and sentiment point of view. In this paper, after the analysis of the web semantic architecture, we describe a framework of sentiment analysis to interpret and extract the sentiment of opinions expressed by people about a product/service, public administrator or law.