Citations and gender diversity in reciprocal acknowledgement networks
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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.
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