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Understanding the Significance of Mid-Tier Research Teams in Idea Flow Through a Community

Bibliographic Data

ID22106961
AuthorsXiaowei Liu (0000-0002-1070-4867, Stony Brook University), Alex Doboli (0000-0003-2472-4014, Stony Brook University), Tom MacCarthy (Stony Brook University), Simona Doboli (0000-0003-0158-4725, Hofstra University)
Year2023
Volume10
Issue6
Pages3422-3432
Publication date2023-12-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2022.3205279
OpenAlexW4312759874
LanguageEN
References cited30

Studying the dynamics of research communities has been an important yet tedious topic. It is important for devising management policies that optimize the quality of research outputs by promoting a certain composition, structure, and interaction patterns for a community. While there has been significant attention to understanding the roles of individuals, there has been less focus on studying the roles that research groups perform and how roles relate to the characteristics of the community. This article presents an experimental study on the roles that research groups have in the idea flow through a community. The study analyzes two facets: the contribution of different kinds of groups to the impact research ideas make on other groups and the importance of specific groups to connect a community together. The results showed that research groups can be classified into four categories depending on the number of received citations. Groups of the mid-tier categories (called categories B and C in this article) are important in tying a community together as they improve the idea impact and bridging between groups. Policies that aggressively eliminate such groups reduce the effectiveness of idea flow, even though research communities include a certain amount of robustness for moderate levels of group removals

Business · Focus group · Knowledge management · Management science · Tying · Complex Network Analysis Techniques · Computer Science · Engineering · Knowledge Management and Sharing · Open Source Software Innovations · Marketing

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