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Acknowledgements in scientific articles suggest not only gratitude, but alsothe interactions among scientists. In this study, we examine theacknowledgement interactions employing data from open-access journals (PLOSseries). We built an acknowledgement network where the nodes represent authorsand acknowledged people, while the links correspond to being mentioned inacknowledgements. Employing motif analysis, we showed how acknowledgementnetworks have developed, and how reciprocal relationships tend to emerge. Tobetter understand these reciprocal relationships, we analysed the reciprocalsub-graphs of acknowledgement from two perspectives: citations and genderdiversity. Firstly, we counted the number of citations, from both reciprocaland non-reciprocal authors. We found that reciprocal authors predominantly tendto cite other reciprocal authors rather than non-reciprocal ones. For genderdiversity, we found that reciprocal pairs that include females tend to emergemore than male-male pairs of reciprocity in various fields, despite the fewernumber of females.

Citations and gender diversity in reciprocal acknowledgement networks