Tons of information is posted everyday on social networks. This information should be summarized in order to be accessible by users. In this paper a novel scheme is proposed for summarizing video content posted on social networks. Towards this direction a probabilistic framework for estimating the location of each post is designed, based on the associated textual content of the post. Furthermore a CLARANS-based key-frames extraction scheme is considered. Then each user is presented with a location-aware summary. The nearest a video is to the location of a user, the more key-frames are extracted. This paper forms an initial study of location-based summarization of video content posted on social networks and experiments on real world data indicate its promising performance.