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Computational applications now go beyond personal computing, facilitating collaboration and social interactions. Social computing is an area of information technology concerned with the intersection of human and social studies connected by computer networks. The primary goal of this article is to provide a brief survey of three popular social computing services: recommender systems, trust/reputation systems, and social networks. We approach these services from a data representation perspective and discuss two of their main challenges: network sparsity and coldstart problems. We also present a novel graph model, which provides an abstract taxonomy and a common data representation model for the three services. We are mainly motivated by the power of graph theory in data representation and analysis for social computing services. Through this model, we believe that it becomes clearer that data from different contexts can be related such that new solutions can be explored; thus, it may provide illumination for the aforementioned problems and stimulate new research.