  Hyperauthorship, a phenomenon whereby there are a disproportionately large
number of authors on a single paper, is increasingly common in several
scientific disciplines, but with unknown consequences for network metrics used
to study scientific collaboration. The validity of co-authorship as a proxy for
scientific collaboration is affected by this. Using bibliometric data from
publications in the field of genomics, we examine the impact of hyperauthorship
on metrics of scientific collaboration, and propose a method to determine a
suitable cutoff threshold for hyperauthored papers and compare co-authorship
networks with and without hyperauthored works. Our analysis reveals that
including hyperauthored papers dramatically impacts the structural positioning
of central authors and the topological characteristics of the network, while
producing small influences on whole-network cohesion measures. We present two
solutions to minimize the impact of hyperauthorship: using a mathematically
grounded and reproducible calculation of threshold cutoff to exclude
hyperauthored papers or fractional counting to weight network results. Our
findings affirm the structural influences of hyperauthored papers and suggest
that scholars should be mindful when using co-authorship networks to study
scientific collaboration.
