Research in Sentiment Analysis has shown rapid progress since late 90s. It is an important research area as analyzing user’s feedback is useful for business analysis, product comparison, counter intelligence, and poll prediction. Despite the rapid surge of Sentiment Analysis research, many unresolved research questions remain. One of the biggest concerns is the Semantic Gap, which involves translating machine understandable form to human understandable form. Though research has been carried out for machine to understand human language, it is still not capable to address the problem mentioned as human languages are diverse and complex. WordNet, for example, attempt to address this issue by incorporating large lexical database for English, with various functionalities to manipulate this database. Recently, WordNet provides multilingual support, which is very helpful to address the diverse human languages. In this paper, we propose a novel multilingual common ontology tool to analyze user’s feedback and opinion. Unlike other existing state of the art tools, our tool is capable of handling multi languages regardless of the webpage layout. Experimental results show that our tool is highly efficient in analyzing opinion from social networking sites.