BEST PAPER NOMINATION
Answering complex questions such as “How do I grow better tomatoes?” often requires individuals to conduct extensive online research and synthesis. Can we crowdsource this complex, high context process with 100 crowdworkers conducting microtasks distributedly? The Knowledge Accelerator uses crowdworkers to extract and synthesize text clips across web pages into coherent articles without a centralized coordinator.
Crowdsourcing offers a powerful new paradigm for onlinework. However, real world tasks are often interdependent,requiring a big picture view of the difference pieces involved. Existing crowdsourcing approaches that support such tasks – ranging from Wikipedia to flash teams – are bottleneckedby relying on a small number of individuals to maintain thebig picture. In this paper, we explore the idea that a computational system can scaffold an emerging interdependent,big picture view entirely through the small contributions ofindividuals, each of whom sees only a part of the whole. Toinvestigate the viability, strengths, and weaknesses of this approach we instantiate the idea in a prototype system for accomplishing distributed information synthesis and evaluateits output across a variety of topics. We also contribute a setof design patterns that may be informative for other systemsaimed at supporting big picture thinking in small pieces.
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