Research on Social Context Acquisition and Reasoning Techniques for Online Social Networks
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Recently, social contexts have been used with promising outcomes in developing social aware applications in different fields. However, a user's social information is distributed over different OSN, which is a challenge for developers wishing to collect this information. Integrating social contexts from these resources can provide such useful applications. In this thesis, a SCWS framework architecture is being proposed. This framework has the ability to acquire raw social contexts from Facebook; an ontology-based model designed for classifying, inferring, and storing social contexts, as a proof-of-concept. In addition, CommonFriends application has been developed that connects with the framework through API to notify users when any of the following scenarios happen: finding common friends, notifying the user of their distance from their friends, when they are within the same location, and suggesting a new friend with common interests. These features will demonstrates the applicability of the research approach. The performance of the mobile application has been evaluated using tester accounts under Facebook's testing environment.