Recent years have seen a thriving development of the World Wide Web as the most visible social media which enables people to share opinions, experiences and expertise with each other across the world. People now get involved in many different social networks simultaneously, which are often large intricate web of connections among the massive entities they are made of. As a result, the challenge of collecting and analyzing large-scale data among social members has left most basic questions about the global composition and function of such networks largely unresolved: What is the essential organization of a social network? who are the influential individuals whose voice is echoed by others? To address these questions, this paper presents an algorithm called sketcher to discover and describe the overall backbone of a specific network. Experimental results on the American College Football, Scientific Collaboration, and Telecommunications Call networks show that sketcher can extract the essential composition of a social network both efficiently and intuitively.
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