This paper describes our system that enables members of a social network to collaboratively annotate a shared media collection. The problem is important since online social networks are emerging as conduits for exchange of everyday experiences. Our collaborative annotation system provides personalized recommendations to each user, based on (a) media features, (b) context, (c) commonsensical relationships and (d) linguistic relationships. We also develop novel concept specificity and abstractness/concreteness measures that further adapt the recommendations to the specific concept. Our preliminary user studies indicate that the system performs well and is more useful as compared to standard web browser recommendation schemes.