Semantic and network evolution in crowdsourced idea refinement

Publication Type

Conference Proceeding Article

Publication Date

12-2020

Abstract

Successful ideation is a cornerstone of development. Advancements in information technology have allowed firms to harness collective intelligence through crowdsourcing ideation. New ideas often undergo iterative development and evaluation during a refinement phase, and only high-quality ideas get accepted for implementation. Therefore, our paper studies how idea refinement influences idea quality from both the content semantics and network structure perspectives, in the context of the online ideation community of TVTropes. For the content revisions of the idea, we examine the influence of semantic stability and convergence. For the network evolution of the idea, we investigate the impacts of refined network centrality and importance of bridging disconnected ideas. We find robust support that semantic convergence in idea content, along with improved network centrality and bridging importance increase idea quality in terms of votes and acceptance. Among these factors, bridging disconnected ideas has the strongest impact.

Keywords

Idea refinement, content evolution, network evolution, idea quality

Discipline

Computer Sciences

Research Areas

Information Systems and Management

Publication

Proceedings of International Conference on Information Systems 2020 (ICIS 2020) ; India, Dec 13-16, 2020.

City or Country

Virtual conference

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