  Acknowledgements in scientific articles suggest not only gratitude, but also
the interactions among scientists. In this study, we examine the
acknowledgement interactions employing data from open-access journals (PLOS
series). We built an acknowledgement network where the nodes represent authors
and acknowledged people, while the links correspond to being mentioned in
acknowledgements. Employing motif analysis, we showed how acknowledgement
networks have developed, and how reciprocal relationships tend to emerge. To
better understand these reciprocal relationships, we analysed the reciprocal
sub-graphs of acknowledgement from two perspectives: citations and gender
diversity. Firstly, we counted the number of citations, from both reciprocal
and non-reciprocal authors. We found that reciprocal authors predominantly tend
to cite other reciprocal authors rather than non-reciprocal ones. For gender
diversity, we found that reciprocal pairs that include females tend to emerge
more than male-male pairs of reciprocity in various fields, despite the fewer
number of females.
