Examining the impact of citation network embeddedness on crowdsourced idea refinement: the moderating role of idea breadth and depth

Publication Type

Conference Proceeding Article

Publication Date

12-2022

Abstract

Idea refinement is a crucial step in the ideation process. Given that ideas are embedded within a network of other related ideas, how the network structure fluctuates throughout the idea refinement process may affect its end outcome. Through studying proposed ideas on TVTropes.org, this research seeks to understand how network embeddedness of an idea's citation network influences the idea quality perception, particularly through degree centrality, betweenness centrality and eigenvector centrality. We also study the boundary conditions of their impact on quality and analyze the moderating role of topic breadth and depth which capture the overall content of the idea. Our results suggests that the positive effect is stronger when the idea topic breadth is lesser, or the idea topic depth is greater. We further explore the mechanism behind these effects by analyzing their effect on change of positive votes and negative votes, showing the influence path might be different.

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 2022 International Conference on Information Systems, Copenhagen, Denmark, December 9-14

Publisher

AIS

City or Country

Copenhagen

Additional URL

https://aisel.aisnet.org/icis2022/sharing_econ/sharing_econ/9/

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