Currently providers are trying to personalize their websites according to user profiles. With respect to the wide variety and great volume of websites, providers look for a design that is more attractive than that of competitors. They look for a unique solution. In this uniqueness, any point such as design, user-friendliness, and content offered to the customer plays a key role in its success. The main objective of this study is to provide profiles of different kinds of users. Later on, this information can be used to design appropriate websites. This kind of information can be explored from social networks. We obtained a dataset of 500 users and we have clustered this dataset to 12 clusters, and then applied Collaborative Filtering on user data to improve the results. The paper will present the corresponding results and provide an interesting overview of different profiles of users in different parts of the world.