作者: Pao Siangliulue , Kenneth C. Arnold , Krzysztof Z. Gajos , Steven P. Dow
关键词:
摘要: A growing number of large collaborative idea generation platforms promise that by generating ideas together, people can create better than any would have alone. But how might these best leverage the and diversity contributors to help each contributor generate even ideas? Prior research suggests seeing particularly creative or diverse from others inspire you, but few scalable mechanisms exist assess diversity. We contribute a new crowd-powered method for evaluating sets ideas. The relies on similarity comparisons (is more similar B C) generated non-experts an abstract spatial map. Our validation study reveals human raters agree with estimates dissimilarity derived our map as much they other. People examples those randomly selected examples. results also corroborate findings prior showing presented who saw set random see this work step toward building effective online systems supporting scale collective ideation.