Semantic and network evolution in crowdsourced idea refinement

• Main Authors: MACK, Zhi Wei Vincent, TANG, Qian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Idea refinement; content evolution; network evolution; idea quality; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/6191
• Institution: Singapore Management University

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.