Mass Collaboration Systems on the World-Wide Web

Mass collaboration systems enlist a multitude of humans to help solve a wide variety of problems. Over the past decade, numerous such systems have appeared on the World-Wide Web. Prime examples include Wikipedia, Linux, Yahoo! Answers, Amazon’s Mechanical Turk, and much effort is being directed at developing many more. As is typical for an emerging area, this effort has appeared under many names, including peer production, user-powered systems, user-generated content, collaborative systems, community systems, social systems, social search, social media, collective intelligence, wikinomics, crowd wisdom, smart mobs, crowd-sourcing, and human computation. The topic has been discussed extensively in books, popular press, and academia (e.g., [31, 32, 25, 2, 36, 17, 3, 7]). But this body of work has considered mostly efforts in the physical world (e.g., [31, 32, 25]). Some do consider mass collaboration systems on the Web, but only certain system types (e.g., [34, 30]) or challenges (e.g., how to evaluate users [14]). This survey attempts to provide a global picture of mass collaboration systems on the Web. We define and classify such systems, then describe a broad sample of systems. The sample ranges from relatively simple wellestablished systems such as reviewing books to complex emerging systems that build structured knowledge bases to systems that “piggy back” on other popular systems. We then discuss fundamental challenges such as how to recruit and evaluate users, and to merge their contributions. Finally, we discuss future directions. Given the space limitation, we do not attempt to be exhaustive. Rather, we sketch only the most important aspects of the global picture, using real-world examples. The goal is to further our collective understanding – both conceptual and practical – of this important emerging topic.