Article ID Journal Published Year Pages File Type
378801 Data & Knowledge Engineering 2015 14 Pages PDF
Abstract

•The paper describes a new user-centered approach for integrating social data into groups of interest.•The approach makes it possible for a group to tap into its members’ social data scattered over different social network sites.•The contents relevant to the group's collectively defined topics of interest are automatically extracted from these data.•Each member is free to personalize his/her collaborative experience within the group.•The paper also presents a working Web-based prototype supporting Facebook, Twitter and LinkedIn.

Social network sites with large-scale public networks like Facebook, Twitter or LinkedIn have become a very important part of our daily life. Users are increasingly connected to these services for publishing and sharing information and contents with others. Social network sites have therefore become a powerful source of contents of interest, part of which may fall into the scope of interests of a given group. So far, no efficient solution has been proposed for a group of interest to tap into social data, especially when they are protected by and scattered across different social network sites. We have therefore proposed a user-centered approach for integrating social data into groups of interests. This approach makes it possible to aggregate social data of the group's members and extract from these data the information relevant to the group's topic of interests. Moreover, it follows a user-centered design allowing each member to personalize his/her sharing settings and interests within their respective groups. We describe in this paper the conceptual and technical components of the proposed approach. To illustrate further the approach, a web-based prototype is also presented. A preliminary test using this prototype was carried out and showed encouraging results.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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