Emergent Remix Culture in an Anonymous Collaborative Art System

artificial intelligence and interactive digital entertainment conference(2021)

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摘要
Many crowdsourcing systems have a contribution model that is shallow but massively parallel, with contributors rarely processing or iterating upon the work of others. Few systems, even those crowdsourcing creativity or artistic talent, are designed to allow deep chains where the ideas of one individual feed into and directly inspire another individual. To explore the ways in which creative ideas arise and evolve under the influence of specific artifacts created by others, we examine patterns from over 50,000 sketches created and uploaded with Sketch-a-bit, a collaborative mobile drawing application in which each sketch is directly prompted by a previous sketch. In this paper, we report results from two analyses of content created in the system's first two years of deployment. First, we apply qualitative coding to survey the range of effort and creativity in user actions (including actions ranging from unintentioned scribbles to subtly inspired reimaginations of source material through the unexpected preparation of blank canvases for others). Second, we perform an exploratory analysis of large-scale behaviors manifest in chains or trees of sketches (such as open-ended conversations and structured gameplay). The intent of this work is to describe an iterative model of collaborative creativity and to demonstrate a range of remixing behaviors that can be expected to arise in unrestricted, anonymous collaborative creativity applications.
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