关键词：数据分析；定制工具；策略；认知复杂任务
摘 要：We examine how analysis tools can be tailored to scaffold novice users into the process of data analysis, encouraging participation and understanding while contributing valuable local insights. Finally, we explore mechanisms for scaling and parallelizing data analysis, even in the absence of a dedicated community or team of analysts. We investigate how individual analysts can crowdsource pieces of social data analysis tasks using paid workers in order to leverage the collective effort of many participants. We demonstrate how large groups of workers can perform cognitively complex tasks like generating and rating hypotheses, and provide tools to help analysts manage the results of this process. These tools and strategies, along with our evaluations of them, highlight the potential of social data analysis in a variety of settings with different kinds of stakeholders. Moreover, our findings suggest leverage points for future social data analysis systems.