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Are We in Agreement? Benchmarking and Reliability Issues between Social Network Analytic Programs Cover

Are We in Agreement? Benchmarking and Reliability Issues between Social Network Analytic Programs

Open Access
|Jun 2018

Abstract

Reliability and validity are key concerns for any researcher. We investigate these concerns as they apply to social network analysis programs. Six well-used and trusted programs were compared on four common centrality measures (degree, betweenness, closeness, and eigenvector) under a variety of network topographies. We identify notable inconsistencies between programs that may not be apparent to the average user of these programs. Specifically, each program may have implemented a variant of a given measure without informing the user of its characteristics. This presents an unnecessary obfuscation for analysts seeking measures that are best suited to the idiosyncrasies of their data, and for those comparing results between programs.

Under such a paradigm, the terms in use within the social network analysis community become less precise over time and diverge from the original strength of network analysis: clarity.

DOI: https://doi.org/10.21307/connections-2017-002 | Journal eISSN: 2816-4245 | Journal ISSN: 0226-1766
Language: English
Page range: 23 - 44
Published on: Jun 4, 2018
Published by: International Network for Social Network Analysis (INSNA)
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2018 Philip J. Murphy, Karen T. Cuenco, YuFei Wang, published by International Network for Social Network Analysis (INSNA)
This work is licensed under the Creative Commons Attribution 4.0 License.