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Network Canvas: Key decisions in the design of an interviewer-assisted network data collection software suite.

Authors :
Birkett, M.
Melville, J.
Janulis, P.
Phillips II, G.
Contractor, N.
Hogan, B.
Source :
Social Networks; Jul2021, Vol. 66, p114-124, 11p
Publication Year :
2021

Abstract

• The Network Canvas suite consists of three applications: Architect ; Interviewer ; Server. • These applications simplify the collection of complex social network data. • Our work prioritizes flexibility, intuitive design, integrated workflow, and collaboration. Self-reported social network analysis studies are often complex and burdensome, both during the interview process itself, and when conducting data management following the interview. Through funding obtained from the National Institute on Drug Abuse (NIDA/NIH), our team developed the Network Canvas suite of software – a set of complementary tools that are designed to simplify the collection and storage of complex social network data, with an emphasis on usability and accessibility across platforms and devices, and guided by the practical needs of researchers. The suite consists of three applications: Architect: an application for researchers to design and export interview protocols; Interviewer: a touch-optimized application for loading and administering interview protocols to study participants; and Server: an application for researchers to manage the interview deployment process and export their data for analysis. Together, they enable researchers with minimal technological expertise to access a complete research workflow, by building their own network interview protocols, deploying these protocols widely within a variety of contexts, and immediately attaining the resulting data from a secure central location. In this paper, we outline the critical decisions taken in developing this suite of tools for the network research community. We also describe the work which guides our decision-making, including prior experiences and key discovery events. We focus on key design choices, taken for theoretical, philosophical, and pragmatic reasons, and outline their strengths and limitations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03788733
Volume :
66
Database :
Supplemental Index
Journal :
Social Networks
Publication Type :
Academic Journal
Accession number :
150082285
Full Text :
https://doi.org/10.1016/j.socnet.2021.02.003