Subfield Effects on the Core of Coauthors

TL;DR

This paper investigates whether the inverse proportionality law of coauthor publications with rank holds within subfields and finds it generally applies to large subfields, with implications for research team evaluation.

Contribution

It extends the coauthor core law to subfields, showing its validity for large subfields and highlighting differences in core sizes across subfields.

Findings

Law holds for large subfields

Small sub-cores suggest different team evaluation considerations

Combining small topics improves statistical analysis

Abstract

It is examined whether the number ($J$) of (joint) publications of a "main scientist" with her/his coauthors ranked according to rank ($r$) importance, i.e. $ J \propto 1/r $, as found by Ausloos [1] still holds for subfields, i.e. when the "main scientist" has worked on different, sometimes overlapping, subfields. Two cases are studied. It is shown that the law holds for large subfields. As shown, in an Appendix, is also useful to combine small topics into large ones for better statistics. It is observed that the sub-cores are much smaller than the overall coauthor core measure. Nevertheless, the smallness of the core and sub-cores may imply further considerations for the evaluation of team research purposes and activities.