Towards Storytelling by Extracting Social Information from OSN Photo's Metadata

The popularity of online social networks (OSNs) is growing rapidly over time. People share their experiences with their friends and relatives with the help of multimedia such as image, video, text, etc. The amount of such shared multimedia is also growing likewise. The large amount of multimedia data on OSNs contains in it a snapshot of user's life. This social network data can be crawled to build stories about individuals. However, the information needed for a story, such as events and pictures, is not fully available on user's own profile. While part of this information can be retrieved from user's own timeline, a large amount of event and multimedia information is only available on friend's profiles. As the number of friends can be very large, in this work we focus on identifying subset of friends for enriching the story data. In this paper we explore social relationships from multimedia perspective and propose a framework to build stories using information from multiple-profiles. To the best of our knowledge, this is the first work on building stories using multiple OSN profiles. The experimental results show that with the proposed method we get more information (events, locations, and photos) about the individuals in comparison to the traditional methods that rely on user's own profile alone.