Is seeing believing?: how recommender system interfaces affect users' opinions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
'Helpfulness' in online communities: a measure of message quality
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Matchin: eliciting user preferences with an online game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Is the Crowd's Wisdom Biased? A Quantitative Analysis of Three Online Communities
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Ranking mechanisms in twitter-like forums
Proceedings of the third ACM international conference on Web search and data mining
What's your idea?: a case study of a grassroots innovation pipeline within a large software company
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The impact of social information on visual judgments
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Measuring the effectiveness of social media on an innovation process
CHI '11 Extended Abstracts on Human Factors in Computing Systems
Voyant: generating structured feedback on visual designs using a crowd of non-experts
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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Idea pipelines enable open innovation within organizations but require the evaluation teams to assess large numbers of ideas. To help filter promising ideas, community voting is often included as part of the pipeline but the outcome of the voting rarely aligns with the ideas selected by the team. To address this problem, we introduce a new scoring model for increasing the findability of promising ideas within idea pipelines. In the model, each participant need only score a subset of the ideas, ideas are scored independently, and the individual scores can be aggregated. We tested the model on an authentic data set and found our model filters ideas chosen by an evaluation team better than community votes.