A user-centered and group-based approach for social data filtering and sharing

We propose a user-centered & group-based approach for social data filtering & sharing.It aggregates user social data across social networks & extracts relevant information.It also allows users to share their social data and intelligence within groups.We describe an extensible system architecture for implementing our proposed approach.We present a web-based prototype and discuss some findings of a primary test. Social networking sites (SNSs) like Facebook, Google+, Twitter, LinkedIn have become a very important part of our daily life. People are connected to multiple SNSs for networking, communicating, collaborating, sharing and seeking for information. Although, the diversity of current SNSs increases and enriches our online experience, they cause some problems. One of the major issues is that users are often overwhelmed by the huge number of social data. It is even worse as these social data are scattered across disconnected SNSs. To address such problems, we propose a user-centered and group-based approach for social data filtering and sharing. First, it allows users to aggregate their social data from different SNSs and to extract relevant contents. Users explicitly define their interests via specific queries, using information filtering techniques, the system will retrieve new corresponding contents. Second, it is expected to extend its first user-centered purpose by allowing group-based information sharing and management. Users can share some part of their own social data with and collectively define the information organization within their respective groups. To describe further and illustrate our proposed approach, a system architecture and a prototype are also presented in this paper. A primary test was carried out and showed encouraging results confirming the added values of our approach.