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

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.