Navigating the Trade-offs between Independence and Collaboration: A Network Analytic Method and Case Study

Zhang, Y; Wu, M; Wang, X; Chen, H

Navigating the Trade-offs between Independence and Collaboration: A Network Analytic Method and Case Study

Zhang, Y

Wu, M

Wang, X Chen, H

Permalink

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2022 Portland International Conference on Management of Engineering and Technology (PICMET), 2022, 00, pp. 1-7
Issue Date:: 2022-09-14

Embargoed

	Filename	Description	Size
	PICMET 2020 AM.pdf	Accepted version	1.04 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Embargoed
Open Access

This item is currently unavailable due to the publisher's embargo.

The embargo period expires on 14 Sep 2024

Full metadata record

Field	Value	Language
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-7731-0301
dc.contributor.author	Wu, M https://orcid.org/0000-0003-3956-7808
dc.contributor.author	Wang, X
dc.contributor.author	Chen, H
dc.date	2022-08-07
dc.date.accessioned	2023-03-17T05:59:09Z
dc.date.available	2023-03-17T05:59:09Z
dc.date.issued	2022-09-14
dc.identifier.citation	2022 Portland International Conference on Management of Engineering and Technology (PICMET), 2022, 00, pp. 1-7
dc.identifier.isbn	9781890843410
dc.identifier.uri	http://hdl.handle.net/10453/167493
dc.description.abstract	Research independence emphasizes the ability to conduct individual work, while collaboration highlights establishing academic connections for team-based activities. Since the two dimensions have become crucial indicators for individual-based research evaluation, how to handle the trade-offs between research independence and collaboration diversity is raised. This paper exploits network analytics to investigate the two indicators via an integrated network that includes an author-term network and a co-authorship network. Specifically, a diffusion-based network analytic model is proposed to evaluate independence by considering the uniqueness of the use of terms, and, in parallel, collaboration diversity is quantified by the strength and breadth of a researcher’s co-authorships. We applied the proposed method to a dataset with 19,612 information science-related articles. The observed results not only well demonstrate the reliability of the proposed method but also empirically uncover a balancing threshold between the two indicators, providing references for researchers and decision-makers in the discipline.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2022 Portland International Conference on Management of Engineering and Technology (PICMET)
dc.relation.ispartof	2022 Portland International Conference on Management of Engineering and Technology
dc.relation.isbasedon	10.23919/picmet53225.2022.9882598
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Navigating the Trade-offs between Independence and Collaboration: A Network Analytic Method and Case Study
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Portland, OR, USA
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2024-09-14T00:00:00+1000Z
dc.date.updated	2023-03-17T05:59:07Z
pubs.finish-date	2022-08-11
pubs.publication-status	Published
pubs.start-date	2022-08-07
pubs.volume	00

Abstract:

Research independence emphasizes the ability to conduct individual work, while collaboration highlights establishing academic connections for team-based activities. Since the two dimensions have become crucial indicators for individual-based research evaluation, how to handle the trade-offs between research independence and collaboration diversity is raised. This paper exploits network analytics to investigate the two indicators via an integrated network that includes an author-term network and a co-authorship network. Specifically, a diffusion-based network analytic model is proposed to evaluate independence by considering the uniqueness of the use of terms, and, in parallel, collaboration diversity is quantified by the strength and breadth of a researcher’s co-authorships. We applied the proposed method to a dataset with 19,612 information science-related articles. The observed results not only well demonstrate the reliability of the proposed method but also empirically uncover a balancing threshold between the two indicators, providing references for researchers and decision-makers in the discipline.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/167493