Social media content has already been used in a variety of applications such as for ranking of news stories, for profiling of user preferences, even for products’ recommendations. However, this type of conversational, user-generated content found in social media, might be used to add value to more traditional event media, such as video. In this paper we examine the capability of automatically producing a meaningful summary of generic videos posted by our social media friends. To do so we take into consideration several parameters such as social graphs, user interactions, video popularity, likes, posts, comments, duration of activity and rate of activity. We believe that these parameters, which can be reliably associated to a given video, have the potential to serve as a powerful form of summarizing data. This paper forms an initial study of one such summarization service and some initial experiments are presented, which indicate the promising performance of the proposed scheme.