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This work consists of developing a platform of sentiments analysis based on a framework that extracts emotions and sentiments expressed by social networks users toward a subject and detects communities and users who influence the obtained results.

Nowadays, the tremendous growth of social networks has attracted the attention of many individuals and organizations, because of the social data made available and easily accessible online, hence our Framework is designed to use online available data of the most popular social networks: Facebook and Twitter, as data source via their official APIs.

We started with a study on social networks by introducing the concept of semantic web and the analysis of sentiments on concepts level, and then we proceed to the approach of the construction of a graph relied on the social data, as well as to make a comparative study of the communities' detection algorithms and to choose the one that suits our problem. These studies enabled us to define the specifications of our project and the document of analysis and computer design. And by the end we moved to the realization phase of the project.