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Online social networks (OSNs) such as Facebook, Twitter, LinkedIn, Google+, have become extremely popular and ubiquitous today. Users are actively connected to these services for creating and sharing contents and events with others, and, in some cases, this activity takes place in the scope of groups of interests. Therefore, from amongst the morass of data generated every day by users, a part of information may match the interests of certain groups. In practice, members are not all linked to each other via each OSN they are connected to. It is also not realistic to assume that each member can manually explore all others' social profiles to reach the information that may be relevant to their interests. Thus, there is a need for aggregating members' social streams on a single information support to collect relevant information, and, consequently, to promote collaborative knowledge-sharing. However, the disconnected nature of today social websites prevents a straightforward aggregation process. An efficient automated aggregation model is needed. We present, in this paper, the idea of empowering collaborative intelligence by the use of a user-centered approach for OSN aggregation. We illustrate the approach by a first experience to evaluate its impact on users information sharing and enrichment capabilities.
International audienceOnline social networks, more commonly called social networks, with websites such as Facebook, Twitter or LinkedIn, have become a very important part of our everyday life. An enormous amount of data is increasingly generated by millions of connected users. These data cover lots of personal and social information including users’ profile information, their current topics of interest, mutual relationships and so on. In this paper, we present a new approach for aggregating such available data with the objective of knowledge sharing and group decision support. The proposed system is able to access, gather, filter and integrate relevant information from social networks, more precisely those published by the members of a given group, into a collaborative knowledge system. Gathered information is centralized and thus accessible to other members at a single place. It can also be combined with other types of information like internal collaborative traces (i.e. member interactions, member activities) and be efficiently visualized for supporting group-related decision-making processes
Over the past years, online social networks with websites such as Facebook, Twitter or LinkedIn, have become a very important part of our everyday life. These websites are increasingly used for creating, publishing and sharing information by users. This creates a huge amount of information a part of which may match the interests of a given group. However the distributed and protected nature of these information make it di cult for retrieving. In this paper, we present a user-centered approach for aggregating social data of members of a group to promote the collaboration and the sharing of knowledge inside collaborative systems. The members will be able to delegate the proposed system to aggregate their di erent social pro les and to make available the relevant part of information to other member of the group
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