Toward Collaborative Ideation at Scale

Abstract

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

Novices Who Focused or Experts Who Didn't?

“…We modeled perceived effort for crowdsourced design feedback, but the approach generalizes to other tasks where users must judge subjective responses from the crowd. Such judgments can be found in work on crowd-based ideation [34], content summarization [17], and social data analysis [36]. Leveraging our methodology from Study 2, including the behavioral data collection and replay tools, researchers and system designers can build statistical models for their own tasks.…”

Data linking over RDF knowledge graphs: A survey

“…To the best of our knowledge, none of the existing approaches evaluate the richness of the obtained joint KB obtained with regard to the IM results. To measure this aspect, new metrics can be defined in line with the idea of the diversity principle in Reference .…”

Semantically Far Inspirations Considered Harmful?

“…To ensure our sampling approach focused on conceptual distance, we also controlled for diversity of inspiration sets (the relative distance between inspirations in a set) because the diversity of inspirational examples has been shown to impact creative performance [4,43]. Conceptual distance and diversity tend to be positively correlated, but it is hard to generate diverse sets for near stimuli.…”

“…From a technical standpoint, significant progress has been made on the problem of how to structure large collections of ideas to enable exploration and navigation of the solution space [1,18,23,33,43,44]. Other studies have explored how dedicated community managers [6] or facilitators [8] might deliver appropriate inspiration to ideators.…”